2020 Annual Review

It's 2021. I'm sitting in a studio apartment. The apartment overlooks bright gold marbled tourist shops & shiny tropical beaches. Clouds streak through the blue sky, like icing on birthday cake. The blistering sun plants patches of red, crusty sun burn on my skin. Ouch.

Last night I ate delicious Omakase, filled with fatty toro, vibrant oysters and crunchy tempura. The chef said, 99% of the people coming in are from San Francisco. Yes, I’m apart of the so called “tech elite” where WFH actually means “Work From Hawaii.”

It annoys me when other tech folks complain about how much 2020 sucked. Most tech business’ are thriving from the pandemic. You make six figures and get to work wherever you want. Calm the eff down.

On the other hand, 2020 was objectively worse than other years. The other part of me, nods in agreement. 2020 did suck. Millions of people lost their jobs. Small business' shut down. Over a million people in the world have died from covid-19.

I constantly remind myself how fortunate I am to be in my situation, especially before setting any goals for 2021.

Highlights

Surfing

I fell in love with surfing after my trip to Sri Lanka in February 2020. Going surfing, is one of the only times throughout the day where I’m completely disconnected. No phone. No computer. No notifications. It’s a spiritual experience. I’m completely present, carefully examining tiny bumps in the water, waiting for the one to fly me to shore.

Friends

Like many, I didn’t meet as many people in 2020. But one benefit, is I felt much more connected with the friends I do have. Zoom calls to stay in touch, calls I never would have set up if it weren’t for the pandemic. Long conversations about life, as we drive to hit a surf spot. “Work-cations” with friends in San Diego & Hawaii.

Career Skills Development

I grew the most in my career in 2020. Not necessarily from a financial perspective, but from a career skill development perspective. I helped develop a variance reduction CUPAC. I switched jobs during the worst of the pandemic and got seven offers. I can now attach the word “Senior” to my title (whatever that means). I’m in more of a “lead” role now, forcing me to grow as a leader as well.

2020 Goals Review

Use data science to generate $XX million of profit for the company

I would say I hit this goal at Doordash. Although, estimating my direct impact on company profit gets convoluted as the company gets larger.

Grade: A-

Level up as a Data Scientist

Although my intention was to level up at the same company, I technically hit this goal by switching jobs. On my current path, I’d start to inch towards a managerial role. I’ll need to carefully think about the path I want to continue on.

Grade: B+

Use writing as a method to level up data science skills by publishing 50,000 words and 20,000 views

I didn't get close to the amount I wanted to publish, which made me question whether I actually cared about this goal. I don’t think this was the right goal. Word count isn’t an effective metric for writing just like how lines of code isn’t a good measure for code quality. Better writing is simple writing. In retrospect, “useful artifacts published” is probably the better metric.

Grade: C-

Find a long-term, compatible relationship

I didn't go on nearly as many dates as I did in 2019. In fact, I only went on a handful as it wasn't a priority of mine while finding a new position. One thing I learned though, is that dating is something that requires momentum. It’s really hard for me to get started once I’ve stopped.

Grade: F

Move to New York City

Although I didn't technically move to NYC in 2020 due to the pandemic, by switching my job to Spotify, I would consider this goal accomplished.

Grade: A

Travel to 5 new cities/countries that I've never been to

I visited Sri Lanka in February 2020 which counts and took a surftrip through Southern California which I'll count as well. Upon reflection, this wasn't a well thought out goal, as I had no strong reason to accomplish this, plus, the pandemic hit in March 2020.

Grade: N/A

All in all I'd say I accomplished 3/6 larger goals I set in the beginning of 2020, which I would consider solid.

What I learned about myself in 2020

I do terribly when people tell me what to do. I excel, when I figure out what to do.

At DoorDash, I wasn't given the freedom to decide what to do. I was told what to do. Many excel being told what to do. I do better when I decide for myself what I need to get done and own the outcome.

I'm not going to be a superstar machine learning researcher.

I'm a big believer in "growth mindset." However, becoming a superstar in any field requires both hardwork, natural talent and innate interest. I thought a lot about this idea of specific knowledge. Specific knowledge is knowledge that’s unique to me and hard to replicate. To develop specific knowledge, I need to leverage my natural strengths, which are:

• Interpersonal/People Skills

• Communication (both written & oral)

• Learn fast, consume information quickly

• Teaching

• Asking Good Questions

• Thinking on my feet

Things that do not come as naturally:

• Engineering

• Multi-tasking (3 or more projects at the same time)

• Context Switching

While a superstar ML researcher might use my strengths of learning quickly & asking good questions, it doesn’t utilize my strengths in people skills.

Working harder isn't the best solution.

Working harder is a solution, but not the best. Working smarter is more important than working hard. But the most important component, is deciding what to work hard on.

I love teaching.

Teaching is the ultimate positive sum activity. Through teaching, someone else gains valuable knowledge and the act of explaining something forces you to deepen your understanding.

Mornings are the best time for personal projects.

I have a lot of trouble working on personal projects after work. Sometimes, I get so into my work, I end up continuously working through the night, at the expense of my personal projects.

I can only focus on one goal at a time.

Too many concurrent goals make it difficult to progress. I can have many goals, but can only focus on one at a time. When I focus on one at a time, I actually make faster progress.

Things to do more of:

Go back to doing more "Challenges" and "Experiments."

Challenges and experiments are a core to my being. Month to Master was both a giant challenge and a series of experiments. Experiments give me the freedom to try & quit things. Structuring projects as "challenges" motivate and inspire discipline for the things I do want to commit to. I’ve gotten away from this:

A few challenges I have planned:

• 66 Days of Data: To continuously up-level my technical skills.

• Some type of creation challenge, where I continuously create/build something + deliver.

A few experiment ideas:

• Youtube Content Experiment: Do I actually like making Youtube videos?

• Plant-based Diet Experiment: How does my health, energy level change if I go completely plant-based?

• Product Manager Experiment: Do I like product work?

Benny Lewis, an Irish polyglot who teaches language learning says: Always have a challenge.

Cooking

I’m not a great cook, but if I’m someone that values health, then knowing how to cook my own meals is vital. Cooking my own meals gives me control over my ingredients which ultimately leads to a healthier lifestyle.

Find ways to teach & share knowledge

Teaching brings me a ton of energy which means I should do more of it. Teaching can be in many forms, 1:1 tutoring, writing blog posts, making youtube videos, writing tweets etc.

Chill

I have a habit of always needing to fill my free time with something productive. I try to fill most of my free time with some type of activity that would advance my goals. I don’t watch Netflix or any TV shows but this year. I’d still like to make progress on my goals, but just be a bit more chilled in the process.

Things to do less of

Delivery/Eating Out

My default habit is to just order something on DoorDash. In line with the intention to cook more, eating out will be something I’ll try to continue doing less of, especially as I aim to eat healthier.

2021 Priorities

To synthesize my 2021 goals, first, I’ll need to map out my list of priorities and then categorize them as a Growth or Maintenance bucket:

1. Career/Business (Growth)

2. Relationships (Growth)

3. Finances (Growth)

4. Health (Maintenance)

5. Fun (Maintenance)

6. Travel (Maintenance)

If my time becomes limited or I set too many goals, this is my priority. I see the relationship component shifting to #1 later this year, after I properly establish myself at my new position.

2021 Outcomes/Goals

This year, I'm going to shift how I approach my goals. As I list them out, it might seem like I'm taking on a lot, but I am not going to be taking them all on at the same time. I'll sequence & slot each goal into different months of the year and re-evaluate them every quarter.

Career/Business

Establishing myself at Spotify by delivering a high-quality product and developing deep expertise

I joined Spotify three months ago. Since I'm fairly new, it's essential that I establish my reputation by delivering high-quality, valuable work. I'm currently working on building an end-to-end demand forecasting system and will be leading a podcast strategic research project. So my initial goal, will be to deliver high quality work and make substantial impact. Through delivery of high impact work, this naturally would open up more doors within the company.

Tactically, this will be done through:

• 66 Days of Data — This project will force me to continue to up-level my data science skillset and build the habit of continuously learning.

• Leadership Reading — On the side, read books focused on leadership, project management. These books might include:

  • Dare to Lead by Brene Brown (Leadership)

  • The Art of Doing Twice the Work in Half the Time by Jeff Sutherland (Project Management)

Start Date: 1/11/2021

End Date: Whenever the project’s delivers

Build a roadmap for my career direction.

This will be my initial focus of 2021. The outcome I want to achieve here, is to have a clearly defined goal/direction I want to take my career. On the current path, I will progress towards becoming a Data Science Manager which is a solid direction. However, I think it's essential to deliberately decide the path I'm on, rather than take the default path. By setting the direction initially, I can take on work on side projects, talk to the right people, to move me in the direction I'd like to go.

Tactically, this will be done through:

1. Mapping out all the different directions I can go.

2. Scheduling calls with people 2 to 3 steps ahead of me.

3. Self-Reflection on the direction I want to go.

4. Run experiment testing my hypothesis

Start Date: 2/1/2021

End Date: 2/28/2021

Cultivate positive serendipity through creating then sharing something useful 1x per week.

My long term goal is to “build my own thing” whatever that means. It’s too vague. Therefore, I need to clarify what this means. However, I can’t clarify this by just thinking about it, I need to make stuff. I picked the word create because this can include code, writing, video, tweets, newsletters or podcasts. As Naval says, "Code and media are permission-less leverage." At minimum, a tweet should suffice here.

A side benefit is this forces me to learn things in the context of usage, which should rapidly improve my learning at the same time. Even if I decide to build something larger, this forces me to find & synthesize learnings. The long term goal, is to use this to plant a seed for the type of business I want to build and to open up unknown opportunities.

Tactically, this will be done through:

1. Coming up with a creation challenge

2. Mapping out a list of ideas + timelines

3. Executing on them.

Start Date: 3/1/2021

End Date: 12/31/2021

Grow Twitter followers to 1000.

This goal is less of a priority. My strategy, will be to just learn and create in public, using Twitter as a form of accountability. My bet, is that by sharing useful information, this will gradually increase my follower count. I'll invest in a little bit of Twitter strategy by purchasing Daniel Vassallo's course, however, I don't plan to invest a ton into "twitter strategy." 1000 is a reasonable number to aim for.

Tactically, this will be done through:

• Synthesizing what I'm learning in the moment into a Tweet

Start Date: Ongoing

End Date: Ongoing

Finances

Review & learn the fundamentals of investing & set myself up for success financially

As I level up in my career, I start to build more and more capital. At this point, I do have sufficient capital to start playing around with investments more. The goal is to better educate myself on evaluating & making investment decisions.

Tactically, this will be done by:

• (Re-)Read The Intelligent Investor

• Read How to Make Money in Stocks

Start Date: 4/1/2021

End Date: 5/1/2021

Relationships

Go on at least 10 dates with the same person.

Romantic relationships was an area I under-indexed in 2020. I’ll be making this a priority in 2021. Learning from before, using # of dates is a poor metric. It promotes shallow relationships and optimizes for as many dates possible. Instead, my goal is to go on at least 10 dates with the same person, to promote a deeper relationship.

Tactically, this will be done by:

• Using dating apps for at least 10 minutes per day

Start Date: Ongoing

End Date: Ongoing

Build a strong, social circle in New York City by hosting at least 4 second-degree dinners.

Second Degree dinner means you have to bring a friend that nobody else who's going knows. I already have friends living in NYC. However, my social base isn't nearly as strong as it is in California, therefore, I'll definitely need to put effort into expanding this network. This would also give me an excuse to learn how to make a few more dishes.

Tactically, this will be done by:

• Using dating apps for at least 10 minutes per day

Start Date: 5/1/2021

End Date: 9/1/2021

Call my family at least 1x every two weeks.

I don't have a good habit of calling my family. This is important, especially because I'm moving to NYC and they're getting older.

Tactically, this will be done by:

• Scheduling in my calendar, on Sundays.

Health

Eat plant-based for two out of three meals per day.

I've run a plant-based diet experiment in the past. I slept better, felt clear headed and more energized. I love meat and want to enjoy eating out with friends as well. Therefore, I'll limit this to two meals out of three in the day.

Tactically, this will be done by:

1. Learning how to make multiple, 15 minute delicious salad recipes

2. Only buying ingredients for these salads

Meditate everyday.

I've been meditating for about 6 years now. However, because I'm working Eastern timezone hours on the west coast, I often start work early (7am). As a result, I end up skipping my morning meditation. I'd like to get this back on track.

Tactically, this will be done by:

• Integrating meditation for 15 minutes, after showering in the morning

Fun

Learn Brazilian Jiu Jitsu

I've always been fascinated with Brazilian Jiu Jitsu. I always resonated with the warrior-scholar archetype. Train both the body and the mind. BJJ looks like the ultimate activity that embodies that warrior spirit. To do this, I'll be signing up for a BJJ gym in NYC, after I move there and when all the covid shenanigans die down.

Tactically, this will be done by:

• Signing up for BJJ in NYC after covid dies down

Learn how to freestyle sing play guitar at the same time

I can already freestyle rap fairly well. I can already play the guitar. I'm neither a good nor a completely garbage singer. The goal is to be able to play a song on a guitar and freestyle sing notes on top of guitar chords. To do this, I will write up an accelerated learning and hire a teacher.

Tactically, this will be done by:

1. Writing out an accelerated learning plan

2. Finding a teacher and signing up for lessons.

Misogi

A Misogi (in the western sense), is where you take on a challenge where you have a less than 50% chance of success. The idea, is to challenge constantly challenge what you believe was possible. This can be in the form of a physical challenge (like run 100 miles) or mental challenge (read 100 books etc). Every year, I require myself to partake in a Misogi.

TBD

Sequencing

Here's how I'm sequencing all these goals. My basic principles for sequencing are:

• I have a single top priority. If push comes to shove, I would have to drop everything else for the top priority.

• At maximum, I can have 4 different projects. My thinking, is that our working memories can only hold up to 4 objects. However, I can only make progress on one goal at a time. Every other project must be a recurring habit.

Habits to Maintain

Continuously up-leveling my data science skillset so I'm effective at my job

For every workday, I should be spending a portion of my workday leveling up my skills. This is a habit I’ve already built and plan to continue through 66 days of data.

Working out everyday

I feel as though my day’s are incomplete if I don’t get some exercise or movement in. I literally feel mental discomfort if I go to bed without having exercised. This is something I’d like to continue.

Reading everyday

I’ve built the habit of reading before going to bed. In fact, it’s a great way to turn off my mind (as long as I’m reading some type of narrative) and quiet down for the night.

Memories

Favorite Books:

• The Almanack of Naval Ravikant by Eric Jorgenson

• How to Decide by Annie Duke

• Grit by Angela Duckworth

Favorite Tweet(s):

Favorite Articles

• How to Do Anything by Justin Kan

• 10 Foundational Practices for the Good Life

Best Lesson(s)

• Just the quality of your thinking and decisions by your process, not the outcome.

• The manager is a multiplier of your experience at work. Great managers 10x your experience and fight on your behalf. Poor managers destroy your experience.

• Find opportunities to get leverage. This involves putting yourself in situations where your strengths can be multiplied or exponentially grow, rather than put yourself in situations were you incrementally grow.

• Find opportunities where you can be a superstar, not just above average. The superstars are the ones who will make 10x someone who is mediocre, rather than just 50% more.

Favorite Books

• How to Decide by Annie Duke

• Grit by Angela Duckworth

• The Almanack of Naval Ravikant by Eric Jorgenson

Favorite Documentary: The Last Dance

Favorite Video: Subway Jam Session

Quotes:

“Writing a story isn’t about making your peaceful fantasies come true. The whole point of the story is the character arc. You didn’t think joy could change a person, did you? Joy is what you feel when the conflict is over. But it’s conflict that changes a person.”

- A Million Miles in a Thousand Years

I got 7 job offers during the worst job market in history. Here’s the data......

Introduction

I got seven data science job offers during the worst job market in U.S history. I’ve completed over a hundred data science interviews, ranging from giants like Apple, Google, Facebook to four person startups. No, I don’t have a Masters or PhD. 

Sometimes, my imposter syndrome asks me what the hell these companies are thinking. I don’t deserve it. Other times, I quietly whisper in my ear that I’m superman and proceed to flex my chest muscles, ripping my shirt to shreds.

Through the process, as a data scientist, I hand-tracked all my data so I could play moneyball with the numbers. Here's what I found.......

High Level Statistics

This table maps out the interview funnel. The white rows, count and conversion, are my numbers. You can see I converted 46% of my onsites to offers and converted about 41% of my applications to phone screens.

The gray portion is the expectation. The expectation acts as a baseline to compare my performance. Stages that dip below the expectation is where I need to improve. You can see, that I beat the expectation at each stage. 

To compute the "expectation", I start with the number of offers I want to target, two. Then, work backwards to figure out what conversion rates I need to target on each stage to hit my desired offer amount.

Let’s dig a bit deeper into those first stages: Applications & Phone Screens. 

How much do years of experience impact my likelihood of getting an interview?

Intuitively, we know that more years of experience should improve our ability to get interviews. But by how much?

I defined interview rate as # of phone screens/# of applications. Basically, how likely was I going to get an interview after I applied to the position?

When I had zero years of experience, my interview rate was 17%. With three years of experience, it was 41%. Each year of experience had increased my interview rate by about 11.5%. Keep in mind, the economy didn't suck three years ago, so I suspect my interview rate would’ve been much higher during a great economy. 

So for anyone just entering a field and is struggling to get interviews, just know that it will get easier as you accumulate more experience. If years of experience matter, the group that’s struggling the most are the entry level applicants. So how many applications should they target?

How many applications should I be sending out to get an offer?

To answer this questions, I developed a new metric called Applications Per Offer or APO. You'll see here, that with 0 years of experience, it took me about 62.5 applications to generate each offer. Compare this to three years of experience, it took me 10 applications to generate each offer.

However, 10 applications per offer is ridiculously low and should not be interpreted as “Oh, I only need to send 10 applications to get one offer.” I’m making a false assumption of the data:

The problem with this metric, is that offers are not independent. Once you get your first offer, your chances of getting a second offer dramatically increase. 

The goal should be getting enough applications in to get to that first offer. Once that first offer rolls in, then we hit a tipping point where other offers start rolling in. Relationship looks more like this:

Unfortunately, I didn’t track timestamps so this curve is based off an eyeball, rather than an actual fit of the data. *Kicking myself…* If we do a rough eyeball of this graph, we see that the first offer hits at around application 50 ish which equates to about 70 to 80% of the total.

So how many applications should you target? As a ROUGH approximation:

1. Figure out the total number of applications you’ll need to send to hit your target offer amount.

2. Multiple that by 80% to get the required apps until first offer.

if you have 0 YOE, let's say you use my 62.5 Applications Per Offer metric. If you wanted to target 2 offers, you'd need 62.5 x 2 = 125 applications. 125 x 80% = 100 applications. Expect to send at least 100 applications to hit that first offer. More, when there’s a poor job market.

Caveats:

• 62.5 Applications Per Offer is based off my own data when the economy was good. It’s likely way, way higher when during a tough market. Later in this post, I talk about how to adjust for economic downturns.

• Every person's situation is different. I know people who've gotten an offer sending only a few applications and some who've sent hundreds of applications with no offers. There is high variance here.

One additional problem to point out, is we’re treating every application the same. In reality there now. Let’s figure out if we can improve our odds with a specific application strategy.

What's the most effective method of applying to positions?

If you're going to aim for 100+ applications, not every application should be treated equally. We intuitively know dropping your resume into the job board blackhole has a terrible response rate. But by how much? Let's look at the numbers.

We’ll use interview rate again (# of phone screens/# of applications) as our core metric. Unfortunately, I didn't record my data for years of experience = 0, so I only have data for the YOE = 1 and YOE = 3. But let’s first assume the interview rates across different methods of applications:

You can see here that the interview rate is around 43% for referrals, 29% for cold e-mails and 6% for direct. If you have 0 YOE, take a haircut off these numbers. Cold e-mail is finding the hiring manager's email address and emailing them your resume. I'll talk about this in a future post.

This graph says that yes referrals are the best channel. However, what happens when we have three years of experience?

With three years of experience, you'll see that across the board, my response rates are higher. But looking at the “Direct” channel, we see a dramatic increase in my interview rates. At zero years of experience, cold e-mails increased my odds by nearly 5x compared to direct. However, at three years of experience, cold emails only increased my odds by 1.3x, which is good, but not amazing.

This leads to the insight that the more experience you have, the better of a response you’ll get through direct applications. With more experience, you have more leeway to go the easy route.

So how should I spend my time?

Figuring out how to spend your time is an optimization problem. You want minimize the amount of time you spend to maximize your ROI (offers). We all know that getting referrals is the best strategy. For a referral, the cost to yourself is <5 minutes writing a message asking for the referral. In return, you get an interview 43% of the time.

If you know someone at the company, even as an acquaintance, it's almost always worth it to ask for the referral.

However, if we don't know anyone at the company, this is where it gets interesting. If I had a choice of either applying directly or through cold e-mails, what is my ROI for each channel? To do this, I built out a simple model:

Assumptions:

• Response Rate to Direct Applications: 2%

• Response Rate to Cold E-mails: 10%

• Probability of Offer given Phone Screen = 12.5%

• Direct Applications take 15 minutes to complete

• Cold Emails take 45 minutes to complete

Pure Direct is purely applying only through direct job boards. Pure email is finding key decision makers at the organization and sending a cold e-mail pitching yourself. 

If we applied 100% of a single strategy, using our simple model, here are the results:

With zero years of experience, writing cold e-mails has the best return on time spent. However, this changes when you have more experience, as the response rate to your direct applications increases. Now, if we were to update our assumptions with my actual response rates with 3 YOE:

You can see here that although cold emails require fewer applications, it requires significantly more time. This leads us to say that, as you accumulate more experience, if your goal is to maximize offer amounts, cold emails may be less and less optimal. 

However, we know that cold emails have a higher response rate. Since they require more time, if you’re more experienced, save cold emails for the companies you love. 

Note: This is a simplistic model that used basic algebra to make these predictions:

def compute_required_hours(time_per_app, response_rate, interview_offer_rate):
    expected = 1
    num_apps = expected/(response_rate * interview_offer_rate)
    
    hours_required = (num_apps * time_per_app)/60
    return hours_required, num_apps

I made it to the onsite. What are my chances of getting an offer?

Let's use some basic probability to figure out your chances of getting the offer.

You've made it to the onsite. Congratulations! Let’s assume, that the onsite has 4 interviews, ranging from behavioral to technical. Typically, you'll need at least 4 yes' to get an offer. However, a single No will result in a rejection.

To make computations simple, let's assume that I knew the right answer to a question 80% of the time and I didn't know 20% of the time. If I knew the right answer, I'd receive a Yes. If I didn't, I'd receive a No.

So with an 80% chance of passing a single interview, the probability that I pass all interviews is 0.80^4, which is 40% chance of getting an offer. Therefore, we'd expect 0.40 offers. To hit one offer, we’d need 2.5 onsites. (2.5 onsites x 40% = 1 offer). 

While this isn't an exact science, even if you're well-prepared, with a probability of 80% of passing each interview, your chances are still worse than 50/50 in getting an offer for a single onsite.

Now, let's throw in another variable: competition. During covid(or some other economic downturn), companies cut headcount so they only have 1 spot available. Now, let's say that you got 4 Yes' but two other candidates got 4 Yes'.

At this point, it turns into a game of chance between you and the other candidates. Since our previous expectation calculation is assuming that 4 Yes’ = an offer, we must normalize our expected offers by the number of competing candidates who also got 4 Yes’. 

So in our example, our expected offers goes from 0.40 to 0.40/3 = 0.13. So if you originally needed 2.5 onsites to get 1 offer, you will now need 7.69 onsites to get one offer. 

In simple terms, if its an ultra-competitive market (like during covid), expect to do 2 to 3x more onsites than usual. I always ask the recruiter how much headcount they have to get my odds. In scenarios with multiple headcount, no need to normalize.

So what’s the best strategy? To increase the total number of offers, your levers are:

1. Raise my probability of passing

2. Complete more onsites

If I raised my probability of passing from 80% to 90%, for a single onsite, this increases my probability of receiving an offer from 40% to 65%. 65% isn't too shabby but can we do better?

However, let's say rather than 1 onsite, we increase our number of onsites to five onsites. Assuming we still have 80% chance of passing, so 40% chance of an offer for a single onsite. This means we have a 60% chance of failing an onsite. The probability that we fail all five onsites is only 7%, which means you have a 93% chance of receiving 1 or more offers.

It’s better to take 40% chance of success five times versus 65% chance of success once. So the insight here is that first, get good enough. Once you’re good enough, your time is generally better spent getting more onsites than raising your probability of passing, unless it’s a company you love.

It’s not worth it to spend 2 hours studying(to improve from 80 to 85%) some obscure thing a company might ask you, compared to getting more shots on goal. 

Takeaways

In the case of job recruiting, it's better to be data-informed than data-driven. There's a lot of nuance in job recruitment. There are some companies you like more and some companies you don't care much about. There are factors such as the economy, job fit, competition, resume, interview skills that result in an offer.

So my recommendations based off the data and personal experience would be:

• If you have a connection for a referral, always ask for it. You have the best odds, even if there’s a chance your connection doesn’t respond to you. 

• If you don't have much relevant experience, your strategy should lean cold e-mails over direct applications. But never  100% direct apps or 100% cold e-mails strategy. Always have at least a small percentage in one channel as an exploration mechanism. 

• If you are on H1-B and have a time limit to find a job, maximizing the number of offers per unit of time spent is the ideal strategy:

  • With fewer YOE, the best strategy is to lean more cold e-mails, referrals than direct applications. If you need a rule of thumb, always go referral. Afterwards, go 80% cold e-mails, 20% direct applications. 

  • With more YOE, you can afford to send more direct applications and just reserve cold emails to companies you love. 

• Be dynamic in your strategy. Don’t rigidly stick to 20% cold e-mails or any type of hard rule. Always gauge the response and the market and dynamically update your strategy. Everybody has a different situation. 

• For companies you love but have no referral, always at least send a cold email. The response rates are still higher than direct applications.

• One area I didn't mention, was if a recruiter reached out to you. If it's a recruiter from the actual company, I'd say take the call. Since they made the move, you're in a position of leverage and you don't have to do any work and your interview rate is close to 1 (compared to 43% referral, 29% cold e-mail etc).

• Your odds are better if you increase the number of onsites, rather than increase your probability of passing. 

Anyways, I hope this post was an insightful look into the job recruitment process. Best of luck and feel free to reach out with any questions! Feel free to reach out on Twitter.

The Four-Step Formula to Solve Any Problem

Fuck. Fibonacci Sequence? I hadn’t heard of that since high school. I didn’t remember what that meant. I didn’t have an analytical degree in college and now I was being tested on it in the interview. I felt stupid.

I botched the interview, using a buggy, inefficient solution. It wasn’t until years later that I learned that fibonacci sequence is standard topic you learn in any data structures & algorithms course. I felt stupid.

But in the case of that interview, if I had just taken a class on data structures, I would have known there are multiple solutions: recursion, memoization or python generators. Failing the interview didn’t mean I wasn’t smart. It meant, I just didn’t take the class yet.

When we see entrepreneurs, engineers solve problems quickly, we assume genius. Richard Feynman has an amazing story of how he beat a man with an abacus using mental math. The reality is, he happened to know a cubic foot contains 1728 inches. The reality is, he happened to know a cubic foot contains 1728 inches because he’s seen so many math problems. 

Solve more problems and you start building a critical mass of problems & solutions. Genius is pattern recognition.

If genius problem-solving is pattern recognition, what does a pattern look like? While, business problems, engineering problems, personal problems may seem different, the problem-solving process is the same in all disparate fields. Yes, you can train “genius” or “intelligence.” 

In 1945, famous mathematician George Polyar published his four step formula toward problem-solving. Here’s the formula:

1. Understanding the Problem

“The formulation of the problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill.”
― Albert Einstein

Failing to understand the problem, is like constructing a puzzle without even looking at the final picture. This is the most important step, which is why I spent more time on this section. Understanding the problem, can be broken down into multiple components:

Data

What information or data do we know to be true about this problem? In math, this would include the definition of the relevant variables. In product, this is actually talking to the users to figure out what they’re struggling with. In business, this is understanding what factors are driving a loss in profit.

Conditions

What condition must I follow within this problem? In computer science, this might mean that your solution must be in linear time. In business, this might mean your solution must be under budget. In design, this might mean your design is limited to 3 different colors.

Assumptions

What assumptions am I making about this problem and can I validate the accuracy of these assumptions?

Every problem, sentence, question, has an inherent assumption behind it. For example, a common business problem is falling profit margin. If we were to solve this problem of a falling profit margin, we are making the assumption that the company cares about profit margin. This assumption could be wrong, in that the company cares about growth, not profitability.

Unknown

What am I trying to solve for? What is unknown?

In algebra, this is the variable we’re aiming to solve for: 10 = 3x + 4. In programming, this is the program we’re aiming to write. In business, this is the strategy or project we’re trying to come up with.

• Is this problem worth working on? What’s the benefit of solving this problem?

• How does the formulation of the problem affect our approach? How does the formulation affect our result?

2. Devising a Solution

Devising a solution is more of an art than a science. At the core, devising a solution comes from our ability to break down the problem into smaller components and using our existing knowledge to find an optimal solution. With experience and proper understanding of the problem, we can recognize components of other solutions that can apply to this problem.

Here are some questions you can use to find the solution:

To find solution(s):

• Can I break this problem into smaller sub-problems?

• Is there a simpler version of this problem that I can solve?

• Are there any related problems that we have optimal solutions for?

• Are there any solutions I can eliminate?

• Can I invert the problem? What would that look like?

• Is there a bottleneck?

• Can I draw this solution out?

• Is there a pattern? What is the pattern?

To optimize the solution:

• What is the most important component(s) this solution should address?

• Is there a simpler version of this solution?

• What are the edge cases of this solution?

• Where can this solution go wrong? What are the risks?

• What would happen at the extremes of this solution?

3. Executing the Solution

Once you have the solution mapped out, then it comes down to execution. We frequently realize mistakes in our solutions after execution, which means we go back to the devising stage. The most important component is to continuously validate whether this is the right step or not.

4. Reviewing your results

Once the solution is executed, our immediate response is to validate our results. The core principle here, is to figure out:

1. Whether this solution works properly.

2. Whether this is the best solution.

3. Other problems this solution can apply to.

Questions you can use to dig into these components:

• Is this the right solution? How can I validate our solution?

• What scenarios would invalidate this solution?

• Does this solution generalize well to other problems? If so, which problems?

• Are there simpler solutions that can give us the same result?

• How will this solution be used?

Not knowing the solution doesn’t mean you’re dumb. It means you didn’t have the requisite tools to solve the problem. For experienced problem-solvers, you’ll probably see that you already follow this process. For inexperienced problem-solvers, this post should outline a framework to tackle most problems, whether you’re in finance, engineering, data science or business.

But regardless of your field, remember that genius is pattern recognition. Remember, It’s not the number of hours you spend solving problems, but the number of problems you solve.

2019 Annual Review

Now that we're two weeks into 2020, the "New Year New Me" motivation wave has crashed. Gyms are no longer crowded. Many have forgotten their new year goals and continue with their merry ways.

Perfect time to publish the annual review post.

During every year review, we cycle through our memories, reliving that amazing adventure we had through the jungles of Thailand, that amazing conversation we had with that stranger on the subway, or that energizing feeling of crushing the work project you've toiled away at.

As I reflected on my favorite moments, books, tweets, movies of 2019, I noticed a single theme: determination. From reading about Alex Honnold's free solo ascent up to El Capitan, to Jose Alvarenga surviving 438 days in the sea, to my own bike trip from San Francisco to LA, everything that caught my eye this year resembled some form of determination.

In 2018, my theme was learning. 2019, it was determination. My theme for 2020? Let’s find out.

To find out what's in store for 2020, I conducted an annual review in this order:

1. Biggest Wins

2. Things to Improve

3. Things to do more of/less of

4. 2020 Goals

5. Habits

6. Memories

Biggest Wins

Biking to LA: Last January, a few friends and I set a goal to bike from San Francisco to Los Angeles. We didn't bike regularly, but we were committed. During this challenge, we overcame a excruciating back pain, patellar tendonitis, 21,000 feet of elevation, 506 miles to complete the challenge.

Career Skill Development: 2019 was the biggest year of growth for my data science career. I've only been working in the field for two years. I also didn't study computer science in college which meant my engineering skills had significant room for improvement. I learned how to write packages, unit tests, build end-to-end machine learning solutions. I also learned how to effectively deal with stakeholders, lead and influence.

Dropping 4% body fat in 1.5 months: In June, I set a goal to get to 15% bodyfat. I crushed it. I started at 17.6% and dropped to 13.4%, while gaining a 1lb of muscle, in about 1.5 months. The recipe for this, was cooking spaghetti squash at home, exercising everyday, and 80% vegetable + 20% meat plates. Oh and biking 500 miles helped.

40 total dates: In 2019, I set an intention to find a long term relationship by dating a lot. I succeeded in the second part. I went on 40 dates over the course of 2019. I made a lot of mistakes and embarrassed myself. I got rejected a lot. I learned to keep first dates cheap and quick. I learned to apply less logic and more intuition. I learned I need to communicate better. Someone can check all the boxes, but just doesn't feel right. But most importantly, I learned what I valued in an ideal women.

Things to Improve

Technical Craft: I don't have a PhD. I don't have a Masters. Being on a team of PhD's, imposter syndrome stands in front of me everyday. But rather than let it crush me, I use it as fuel to become better than ever. While my technical skills aren’t terrible, I'm holding myself to a higher standard. To be completely honest with myself, compared to my teammates, my technical skills are definitely on the weaker end.

Dating/Relationships: While I did go on 40 dates last year, I didn't accomplish my goal: find a long-term compatible, relationship. I went hard on dating for the first eight months. For the last few months of the year, I stopped dating as frequently since I was burnt out. I’ll need to put myself in situations where I can meet women who have aligned values.

Leadership/Influence: At work, my main focus has been on execution and less on leadership side. A focus for next year, will be on how to have my ideas be heard, effectively sell them and be able to positively influence the organization. This also means thinking from first principles to challenge ideas before accepting them. The first step, is to flawlessly execute. This builds trust and creates political capital to have influence.

Things to Do More Of:

What were the experiences that triggered the highest number of flow states in 2019? What were the experiences where I lost track of time? This is what I need to do more of.

Surfing: I'm a beginner/intermediate-ish surfer. Whenever I catch a wave while surfing, the ocean drowns away all my worries as it pushes me to shore. It's ecstatic. Surfing is the on activity I must do when I’m feeling burnt out. There’s something magical about being out in the ocean, no technology, just you and mother nature.

Cycling: If you want to train “determination”, I recommend cycling. The repetitiveness of cycling turns it into a meditative sport. The repetition forces you to calm your mind, pay attention and most importantly, to just keep going. Although this year’s theme won’t be determination, I’ll need to continue applying determination to my newer goals.

Meaningful conversations: The most meaningful conversations are the ones that touch our hopes, fears, dreams. They shine light on our imperfections with the other person listening intently, absorbing every word and emotion floating in the atmosphere. Whenever I have amazing conversations, I leave them feeling energized.

Data Science: Over the last few months, I've been enjoying data science more than ever. The process of thinking deeply about a problem, finding a solution and seeing results triggers an odd, light buzz throughout my body. Constantly grinding, then solving a problem, makes me want to jump on a table and pound my chest, giving a Tarzan-like scream.

Writing: I didn't write as much as I wanted this year. I wrote a giant post about my bike trip but stopped right after. Not only is writing a great flow activity, but it's also a great way for me to hone my thinking and understanding of ideas. But most importantly, writing is an amazing way of sharing what I’ve learned with others.

Things to Do Less Of:

Binge Drinking: I used to party a lot in my college years. This year, I can count on one hand, the number of times I had a hangover. This is great and I plan to keep this up. The times where I notice myself becoming irritable, upset or anxious are usually after nights of heavy drinking. I still plan to have a couple drinks. However, as I get older, binge drinking doesn't really have a place in my life. Unfortunately for my friends who love to binge drink every weekend, this may mean we grow apart.

Ordering Take Out: I habitually order delivery. This isn't great for my wallet and my health. While I don't eat crappy food, ordering out usually means I don't know what's actually going into my food. The solution here is to cook at home more often.

2020 Theme - Craftsmanship

Based off my 2019 reflection, my 2020 theme will be on craftsmanship. Like a blacksmith welding metal, the craftsman pay attention to the minutiae of everything they're building. They pursue their craft with the highest standards of excellence. Excellence means we hold ourselves to a higher bar than others expect of us. You pay attention not just to how it looks on the outside, but the inside. You take feedback but its the only way to improve.

Combine 2018's theme of learning with 2019's theme of determination and we get “craftsmanship”. The principle here is to treat all my projects as a part of my "craft." Not just work, but any personal projects. This is the pursuit of excellence.

Outcomes/Goals

Use data science to generate $XXX of profit for the company: I won't put an exact number publicly, mainly because the number is based off internal information. But, by aligning my goal with the companies, this means any work I do will not only entail using data science, but also understanding the business impact of the project I work on.

Level up as a Data Scientist: While I won't divulge my data scientist leveling, my goal here will be to level up my skills so they hit the next level. This means working on additional projects related to relevant topics outside of work. This may include heterogeneous treatment effects, deep learning, chat bots. Ideally, this goal would build off the first goal. By building valuable projects, I can accomplish two goals at the same time.

Use writing as a method to level up data science skills by publishing 50,000 words and 20,000 views,: I'm a better writer than most data scientists. Combining data science with writing is how I leverage my stronger communication skills. Clear writing is clear thinking. And if i can apply writing to my data science skills, this forces me to clarify my ideas within data science. 50,000 words comes to a 1,000 word post bi-weekly. This would give me enough buffer to also building projects that I can write about.

Find a long-term, compatible relationship: The key here will be to continue taking swings. I'll only need one to accomplish this goal. To do this, I'll also need to put myself in situations with people who have similar values to tackle the compatibility component.

Travel to 5 new cities/countries that I've never been to: I didn't travel much last year. Outside of snowboarding in Japan and biking to LA, I stayed put in the Bay Area. I've traveled quite a bit out of the country, however, I've never been to cities like Chicago, Austin and Seattle. This year, I plan to visit at least 5 new places outside of California. I currently have a trip planned to Sri Lanka.

Habits

Connect w/ people who have similar values: This ties well with my dating goal. The only difference, is that the focus isn't just on meeting women, but meeting people who have similar values. So far, the best place has been through the internet, especially online communities. If I have an obscure interest, I can always count on someone on the internet to have the same interest. How can I find similar communities in real life?

Spend more time in flow sports: surfing, cycling, snowboarding: Sports is my favorite flow activity outside of work. Since my work is extremely analytically focused, it'll be important for me to engage in activities that use my body outside of work. Sports that get me into flow are surfing, cycling and snowboarding. However, sports that I also enjoy include football, basketball, tennis. Do more of this.

Cleanliness: Over the years, I've significantly improved. From our cock-roach infested college apartment 6 years ago and now somewhat maintain a clean room. However, cleaning still feels like a chore. Adopting Marie Kondo's attitude toward seeing cleaning as a way to "spark joy" will be key.

Memories

Favorite Tweet(s): High Agency Behavior

Favorite Article(s): Bus Ticket Theory of Genius

Favorite Song: Trippy by J. Cole

Favorite Video: Mac Lethal performs poem from 84 Year Old Man

Favorite Movie: Free Solo

Biggest Challenge: Biking to Los Angeles on Patellar Tendonitis

Favorite Sports Moment: Klay Thompson draining his free throws after tearing his ACL.

Favorite Book: 438 Days

Favorite Course: The Wim Hof Method

Favorite New Artist: Justice Der

Favorite Quote(s):

It's about being a warrior. It doesn't matter about the cause necessarily. This is your path and you will pursue it with excellence. You face your fear because your goal demands it. That is the god damn warrior spirit. - Alex Honnold

"When you’re told that something is impossible, is that the end of the conversation, or does that start a second dialogue in your mind, how to get around whoever it is that’s just told you that you can’t do something?" - Eric Weinstein