Ask me
  • How to prepare for a data scientist job interview.
  • How to build a successful tech career.
  • How to build large-scale machine learning systems.
Introduction
  • Founder of instamentor.com, posturenet.app and sqlpad.io
  • Most recently a senior manager at Apple, where I built and hired a world-class machine learning team of data scientists, software engineers, data engineers, and product managers.
  • Head of data science at Chegg, research scientist at Amazon, serial entrepreneur.
Experience
  • 2017 - 2020, Senior Manager of Machine Learning, Apple
  • 2014 - 2016, Lead Data Scientist, Apple
  • 2013, Head of data science, Chegg
  • 2011-2013, Research Scientist, Amazon
  • 2007-2010, Data Mining researcher at a few startups.
Education
  • Master of Science in Applied Mathematics, Ph.D. dropout.
  • College of William and Mary
Fun fact
  • I started coding when I was in primary school.
  • 80% of the startups I worked at got acquired by an F1000 company.
Social

Hi Leon and Mike,

Just wanted to share, I accepted an offer from A____ as a Data Engineer and wanted to offer a huge thank you to both of you guys.

Even though I only shared a small time with you both I benefited a lot from your platform and your mock interviews.

Some of the questions you gave during our Data Modeling with you Mike were presented verbatim.


- Steve

Hello Leon ..I just want to say thanks, your platform helped me land 3 offers ".


- Jonathan

I signed up on Leon's service and was pleasantly surprised when he helped me out personally on the website. In two mock interviews with him from instamentor.com, he was meticulously prepared and very professional.

Throughout the interview he provided fantastic feedback and frameworks on how to be better prepared for both technical and behavioural aspects of an interview. He is also a very positive and friendly person and I enjoyed all my interactions with him.


- Rahul

I recently graduated from a top Ivy League university with a Ph.D. in Biology.
I have no idea what to do with my career or how to start looking for a job.

Thanks to Leon's help, I recently got a data scientist job offer from a tech company.
I can't thank Leon enough, you need to hire him!


- Jenny

Mock interview with Leon Wei

9 services

A/B testing is a statistical framework that helps validate an idea or a theory through data.

For example, a product manager wants to know if changing the color of a buy button from green to blue can encourage more purchases. As a data scientist, it is your job to work with the product manager and, quite often, the engineering team(can help implement the testing settings) to develop a testing plan.

You need to decide at least how many people will see the different colors of the button (sample size), and how many days will the testing run (usually multiples of a week, 7 days), and where should it be running (the US only, or some other small countries just in case testing group is a failure, you don’t want to have a very negative impact to the revenue).

The key assumption of A/B testing is that the control group and the testing group have to be independent. You will probably be asked several questions around this assumption.

You will also need to understand key concepts such as novelty effectlearning effectA/A testing, Simpson’s paradox, etc.

Sample question

The engineering team just invented a people-you-may-know widget. If it is implemented, a user will see their friends on the right-left corner of their homepage. How do you design an experiment to decide whether we should launch this feature or not?

View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ A/B Testing with Leon Wei for $399

Introduction

Before heading into a real software engineering interview: whether it is a phone screen, or during a final round.

It is crucial you have bug-free code developed in a short period of time.

The best way to achieve a bug-free code is through rigorous mock interviews.

How it works

Our mentors have done hundreds or thousands of real interviews at top tech companies such as Google, Facebook, Apple, Amazon, they will emulate a real job interview process when your mock interview is conducted.

You will have a conversation that resembles a real interview as closely as possible, in the end, you will also have the opportunity to receive feedback from your mentor.

What you will get

Gain a simulated interview experience to get a feel of how it works.

Get over nervousness after you've done a few mock interview practices.

Valuable feedbacks during and after the mock interview provided by your mentor.

Become confident and get familiar with the interview process.

How it's conducted

You will be asked a series of coding questions (mostly based on data structures and algorithms) customized towards your dream company, please make sure you share the job descriptions with your mentor, so the questions can be customized towards your dream job.

And you will be writing code in a browser where your mentor can see your coding in real-time. 

A link to access the code editor will be provided before or at the beginning of the interview process.

 

Practice makes dream offers! Let's book your Software Engineer Mock Interview today!

Tell your mentor what programming languages you would like to use (e.g., Python, Java, C++) when you book this session.


“Interviewed and hired many software engineers, front end, back end, full-stack, machine learning engineers in the past few years at companies like Apple.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Algorithm | Data Structure with Leon Wei for $299

Behavioral questions or leadership interview questions are probably the most frequently asked questions during a job interview.

However, I've interviewed so many talented data scientist candidates at a FAANG company. Some of them are very smart, did really well answering technical and coding questions, but they still didn't get their dream job offers. Why?

Because they didn't prepare behavioral questions and didn't know how to answer them,  which in the end, cost them their dream jobs!

Trust me, even if you are only interviewing for a technical job, behavioral questions still matter significantly, and you need to be well prepared, don't ever overlook them.

Behavioral questions may sound intimidating, and some of the questions may catch you off guard or even annoy you if you are not seen them before

But if you follow the strategy outlined in this tutorial and keep practicing those 9 types of behavior questions, you will nail them in your job interview.


“I have conducted many rounds of BA or LP interviews at companies such as Amazon or Apple. Happy to help you prep yours.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Behavioral Questions | Leadership with Leon Wei for $299

Data modeling is often asked for data engineer, data warehouse architect, or software engineer positions.

Good data modeling is essential for a consistent, efficient, bug-free, and long-lived data environment.

Make sure you are super familiar with concepts such as Dimensional   Modeling Star  Schema,  Snow-Flaked  Schema.

It’s possible to solve any given data request in an almost limitless number of ways, but when data needs to be extensible and maintainable throughout the systems, a good data model is critical to success. When it comes to handling a business requirement with an ability to handle large data,  a  deeper understanding of normalized  (Third  Normal  Form)  and denormalized design.


“I have interviewd and hired a dozen data engineers at tech companies such as Apple, Amazon.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Data Modeling with Leon Wei for $299

 

Machine learning-related roles, including Research Scientist (Amazon, Google), Data Scientist / Algorithm (Facebook), and Machine Learning Engineers, are highly paid. Super fun often involves working with state-of-the-art algorithms.

The hiring process could be highly competitive. Not only will you be asked to be an excellent programmer (easy, medium levels of algorithm questions for sure), but you also need to know machine learning theories and experiences such as model parameter fine-tuning.

You will want to brush up on your machine learning skills if you want to succeed in a data science interview. A good place to start is with Andrew Ng's Coursera Machine Learning course.

You may also be asked topics such as CNN, NLP, reinforcement learning, computer vision, depends on the specific roles.

Deep Learning, The topic of deep learning, is in high demand in the data science world, and it is one of the key things that you want to brush up on if you are interested in pursuing a career in data science. There are a couple of good courses that you can check out, like Stanford's CS231n course.

Natural Language Processing (NLP) is an area in data science that is in high demand and will only become more so as we move further into the 21st century. NLP allows us to analyze text, whether spoken or written and derive useful information from it. If you want to be a successful data scientist, you want to work with NLP. This is a great area to pursue as a side project.

 

 


“Ex senior manager of machine learning at Apple, hired teams of world-class researchers and engineers in machine learning and AI.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Machine Learning with Leon Wei for $399

One of the data scientists’ main responsibilities is to extract insights from data and work with product managers and engineering teams to deliver actionable plans to improve the product. Think about how you would measure the success of different parts of the product. Why do you think the placement of the text box is at that specific location? What can you do to improve it?

The interviewer will try to evaluate your ability to apply data to the real product problem, how you systematically approach and structure the problem, form a hypothesis with reasonable assumptions, design, and test hypotheses through A/B testing, and use data and facts to convince others to adopt your recommended approaches.


Product Sense sample questions

  • If revenue dropped in a given week, what metrics would you look at to understand and why?
  • How would you measure the health of our product search functionality?
  • How would you measure the success of Uber Eats' search bar? How can we improve it? If we move the search bar to a different position, what metrics can we use to evaluate their performance? How would you convince the product manager to move forward with your design of the experiment?

How does product sense mock interview work?

  • After a successful payment, you will be redirected to the mentor's calendar page, where you can book a meeting immediately.
  • You will get a chance to specify the types of companies and roles in the meeting invite to help a mentor better prepare for the mock interview.
  • The mock interview will be conducted through a Zoom meeting.
  • After the mock interview, your mentor will send you detailed feedback through email so you can improve.

Product sense mock interview sample feedback

Hi Jimmy,

Happy Friday!

Great meeting you today, I think your A/B testing knowledge is excellent, and I hope you continue working on your A/B testing by watching the Udacity Course.

We did a few questions, and here are some areas that I think still have room to be improved:

1. Process and the formula to estimate the minimum sample size to run A/B testing;

2. Edge cases in A/B testing and how to deal with them:

  1. a. Novelty effect; (you did a great job by applying the testing to new customers);

  2. b. Simpson’s paradox

3. One use case we didn’t get a chance to cover is short-term vs. long-term effect. For example: if we run an extensive promotion campaign and offer more discounts on a test group B, it’s straightforward to know that group B is a winner, but for the long term, it might hurt the business because people just wait for more coupons or discounts.

Further reading:

Lean Analytics is an excellent book to read if you have some time.

It focuses on the early stage of a startup and growth. Since most tech companies in silicon valley still consider themselves as startups, the framework described in this book could be extremely useful.

When thinking about product-related questions, I tend to categorize them into two categories (existing product or new product). But, perhaps it could also help you.

1. Existing product/feature:

  1. Evaluating the existing products/features or something we just launched.

Sample questions:

We just launched a new messaging app/ people you may know feature/ new recommendation engine. How do we know if they are working well, what metrics you want to use, and why?

  1. Optimizing/Improving the existing products, which metrics should we try to move, and what are the actionable steps?

Sample questions:

  a. How do we improve Facebook advertising?

b. We found that the short-term video is not doing well in Latin America. How can you improve it?

c. How can we improve our customer’s lifetime value? (How do you compute a customer’s lifetime value in the first place? For example, consider ltv = monthly customer spends/monthly churn rate. We can either improve monthly spending or reduce the churn rate to improve it.

2. New product/feature

Product decision

Whether to make changes to an existing product or something brand new?

The goal should still tie to the company growth, think about whether the new feature/changes/new products will help improve growth: a. acquiring new users and b. reduce churn of existing customers.

Sample questions:

a. Should we add a dislike/love/downvote/upvote button on Facebook/Instagram/etc.?

b. Should we do two-step verification when the user register in our app?

c. Should we allow people to make a re-purchase without re-authenticating?

Thanks and have a great weekend. Let me know if you have any questions.

Leon

View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Product Sense with Leon Wei for $399

SQL is a must-have skill for any data-related role. Including data scientists, data analysts, data engineers, or even software developers, very often your future employee will verify your ability to process and manage data.

As the #1 language in the industry for data management, SQL skills are probably one of the most important to master before starting an interview process. 

The SQL interview can bear other names and may be called  Technical Analysis or Data Interview during a FAANG company interview, you might be asked to perform a series of SQL operations to extract data and insights, and answer follow-up questions about their products.


How does a SQL Mock Interview Session work?

Before your 'real' interview, it will be super useful to do some mock interviews with an experienced mentor to get you ready.

Our mentors have done hundreds or thousands of real interviews, they will try to emulate a real job interview process.

You will have a conversation that resembles a real interview as closely as possible, in the end, you will also have the opportunity to receive feedback from your mentor.


What you will get from a SQL Mock Interview?

✅ Experience a simulated SQL interview experience and get a sense of how the FAANG company interview process is like.

✅ Get over nervousness after you've done a few mock interview practices.

✅ Valuable feedbacks during and after the mock interview provided by your mentor.

✅ Become confident and get familiar with the interview process.


How it's conducted

You will be asked a series of SQL questions customized towards your dream company, please make sure you share the job descriptions with your mentor, so the questions can be customized towards your dream job.

And you will be writing SQL queries in a browser where your mentor will be able to see your coding in real-time. 

A link to access the SQL code editor will be provided before or at the beginning of the interview process.


Sample SQL Mock Interview feedback

Hi Jimmy,

Great chatting with you yesterday. Here are some notes about the next steps. Overall I really enjoyed our skills assessment session and your answers (still room to be improved, but I think you probably will only need one month to get ready). 

So let's spend our next session evaluating your Python/Pandas/Machine Learning and Behavioral questions. 

Let me know if you have any questions.

Cheers,

Leon

 

Jimmy skills evaluation Part 1 (SQL, Product Sense)

SQL

Current level: 4.5/5

Notes: Jimmy already has excellent SQL skills. She understood the difference between ROW_NUMBER and RANK functions and quickly came up with a query solution. However, there is still room to be improved, e.g., using full outer join and code formatting.

Next steps: For November, Jimmy should continue practicing SQL on SQLPad or Leetcode to maintain a good status.

 

Product Sense

Current level: 4/5

Notes: Jimmy already has some excellent ideas on answering Product Sense questions and has an initial framework to answer those questions. 

 

Next steps: (in priority)

1. We need to strengthen Jimmy's domain knowledge in advertising since companies such as FB, Google, and TikTok's revenue mostly come from advertising.

Different types of ads network (search, social, video ads) and monetization models: e.g., impression-based (CPM: cost per thousand impressions) vs. performance-based (CPC: cost per click).

An excellent place to start is iab.com, as well as Google and FB's earnings report.

2. Read the cracking the PM interview Chapter 10 (learn how to do company research) and Chapter 14 (product questions), 15 (solidify the framework).

3. Jimmy can also start reading or watching more technology news. Some of the great places to start are techcrunch.com, Bloomberg technology, daily newsletters such as hustle. Co to immerse herself with creative product ideas, latest industry trends, and well-versed in latest technologies.

 

Other areas:

1. Technical: noticed sometimes it's a bit hard to hear clearly from Jimmy, and perhaps it's because the speaker was blocked, or was there a poor internet connection? We should fix this to make sure an interview can hear Jimmy clearly for the actual interviews.

2. Resume: You need to spend some time reviewing and working on your resume improvement. It's already an excellent copy.

3. LinkedIn (optional): we can spend some time improving your LinkedIn profile.

4. Github (optional): not super important, but it could be helpful to have a public Github account with some sample project codebase.


Practice makes dream offers! Let's book your SQL Mock Interview today!

Tell us what programming languages you would prefer to use when you book this session.


“I have interviewed hundreds of candidates in the last 10 years at tech companies such as Apple, Amazon & Chegg. Happy to share my feedback and help you succeed in your SQL interview.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ SQL with Leon Wei for $299

System design questions are commonly asked during software engineer and data engineer interviews.

When interviewing at top technology companies, very often you will demonstrate your skills and abilities to convert a prototype into a large-scale, internet application.

System design takes many years of real work experience to be really good at it, and to a large degree, your performance in system design can determine your 'seniority' or 'levels' for your overall offer package.


“I've interviewed and hired software engineers, software architects, built several large-scale machine learning software systems at companies such as Apple, Chegg, Amazon, and startups.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ System Design with Leon Wei for $299

Virtual Onsite interview or Final Round interview is usually a 4-6 hours long process, not only mentally challenging but also physically demanding.

To help our users best prepare for their dream company job interviews, we are excited to launch an onsite mock interview service, which simulates a real onsite interview experience to help you become 100% job interview-ready.


Virtual Onsite Mock Interview FAQ

1. Which company/role's onsite mock interview service is available?

We currently offer the following roles: data scientist, software engineer, data engineer, machine learning engineer, product analyst, and business intelligence engineer.

You can almost request any technical roles in data, software engineering, or machine learning related. We have a very strong team of mentors from major tech companies including FAANG.


2. How does virtual onsite mock interviews work?

  1. Upon successful payment, our team will reach out to you and schedule a free quick chat to understand your needs;

  2. Our team will assemble a team of 4-5 mentors who all have hiring experience, based on your specific needs, to form a hiring committee.
  3. We will schedule the mock interview for a weekend (mostly Saturday), and it will last about 4-5 hours.
  4. you will meet 5 different mentors (all have hiring experience) that form a hiring committee and receive detailed feedback, including hire or no hire decisions.

3. What will you get from a virtual onsite mock interview?

Depending on the company/role, you will meet 4-5 different experienced hiring managers and senior individual contributors, which simulate a real final round interview process.

Those mentors will be carefully selected by our team to best represent the company and role you are interviewing with.

After the onsite mock interview, every interviewer will submit their feedback, and you will receive comprehensive feedback documents within 24 hours on how to improve your interview skills.


4. Will I get a refund?

Absolutely! As long as you give us at least 48 hours (2 days) notice, we will refund you 100%. If you didn't show up and didn't notify us, we will not be able to refund you.


5. Can I cancel/reschedule?

Absolutely! As long as you give us one week's notice, since our mentors are all busy as you, and it's really hard to coordinate everyone's time. Once it's scheduled, we would like to ask that you try keeping the originally planned mock interview if possible.


Sample Virtual Onsite Mock Interview Process:

1. Facebook data scientist virtual onsite mock interview:

  1. Analysis: Product. KPIs to evaluate a new feature/product (45 minutes);
  2. Analysis: Applied data. Engagement dropped 15 percent. What would you do? (45 minutes);
  3. Quantitative analysis: probability, prior/post probability, a/b testing (45 minutes);
  4. Technical analysis: SQL (45 minutes);

2. Amazon data scientist virtual onsite mock interview:

  1. SQL & data modeling: write a query to recommend products that can be used for subscription services. (1 hour);
  2. Machine Learning: how to prevent over-fitting, how to measure variable importance? (1 hour);
  3. Leadership/Behavioral questions, aka bar raiser interview. How do you handle an impossible deadline? (1 hour)
  4. Statistics. How do you explain the p-value to non-technical people? How do you handle Simpson's paradox?  (1 hour).

Sample onsite mock interview feedback:

Jimmy skills evaluation Part 1 (SQL, Product Sense)

SQL

Current level: 4.5/5

Notes: Jimmy already has excellent SQL skills. She understood the difference between ROW_NUMBER and RANK functions and quickly came up with a query solution. However, there is still room to be improved, e.g., using full outer join and code formatting.

Next steps: For November, Jimmy should continue practicing SQL on SQLPad or Leetcode to maintain a good status.

 

Product Sense

Current level: 4/5

Notes: Jimmy already has some excellent ideas on answering Product Sense questions and has an initial framework to answer those questions. 

 

Next steps: (in priority)

1. We need to strengthen Jimmy's domain knowledge in advertising since companies such as FB, Google, and TikTok's revenue mostly come from advertising.

Different types of ads network (search, social, video ads) and monetization models: e.g., impression-based (CPM: cost per thousand impressions) vs. performance-based (CPC: cost per click).

An excellent place to start is iab.com, as well as Google and FB's earnings report.

2. Read the cracking the PM interview Chapter 10 (learn how to do company research) and Chapter 14 (product questions), 15 (solidify the framework).

3. Jimmy can also start reading or watching more technology news. Some of the great places to start are techcrunch.com, Bloomberg technology, daily newsletters such as hustle. Co to immerse herself with creative product ideas, latest industry trends, and well-versed in latest technologies.

 

Other areas:

1. Technical: noticed sometimes it's a bit hard to hear clearly from Jimmy, and perhaps it's because the speaker was blocked, or was there a poor internet connection? We should fix this to make sure an interview can hear Jimmy clearly for the actual interviews.

2. Resume: You need to spend some time reviewing and working on your resume improvement. It's already an excellent copy.

3. LinkedIn (optional): we can spend some time improving your LinkedIn profile.

4. Github (optional): not super important, but it could be helpful to have a public Github account with some sample project codebase.

 


Hi Jimmy,

Happy Friday!

Great meeting you today, I think your A/B testing knowledge is excellent, and I hope you continue working on your A/B testing by watching the Udacity Course.

We did a few questions, and here are some areas that I think still have room to be improved:

1. Process and the formula to estimate the minimum sample size to run A/B testing;

2. Edge cases in A/B testing and how to deal with them:

  1. a. Novelty effect; (you did a great job by applying the testing to new customers);

  2. b. Simpson’s paradox

3. One use case we didn’t get a chance to cover is short-term vs. long-term effect. For example: if we run an extensive promotion campaign and offer more discounts on a test group B, it’s straightforward to know that group B is a winner, but for the long term, it might hurt the business because people just wait for more coupons or discounts.

Further reading:

Lean Analytics is an excellent book to read if you have some time.

It focuses on the early stage of a startup and growth. Since most tech companies in silicon valley still consider themselves as startups, the framework described in this book could be extremely useful.

When thinking about product-related questions, I tend to categorize them into two categories (existing product or new product). But, perhaps it could also help you.

1. Existing product/feature:

  1. Evaluating the existing products/features or something we just launched.

Sample questions:

We just launched a new messaging app/ people you may know feature/ new recommendation engine. How do we know if they are working well, what metrics you want to use, and why?

  1. Optimizing/Improving the existing products, which metrics should we try to move, and what are the actionable steps?

Sample questions:

  a. How do we improve Facebook advertising?

b. We found that the short-term video is not doing well in Latin America. How can you improve it?

c. How can we improve our customer’s lifetime value? (How do you compute a customer’s lifetime value in the first place? For example, consider LTV = monthly customer spends/monthly churn rate. We can either improve monthly spending or reduce the churn rate to improve it.

2. New product/feature

Product decision

Whether to make changes to an existing product or something brand new?

The goal should still tie to the company growth, think about whether the new feature/changes/new products will help improve growth: a. acquiring new users and b. reduce churn of existing customers.

Sample questions:

a. Should we add a dislike/love/downvote/upvote button on Facebook/Instagram/etc.?

b. Should we do two-step verification when the user register in our app?

c. Should we allow people to make a re-purchase without re-authenticating?

Thanks and have a great weekend. Let me know if you have any questions.

Leon


“You will first book a 45 mins chat (FREE) with me to collect requirements. Our team will then assemble an onsite mock interview team: 4-5 experienced mentors and set up this 4 -5 hours-long onsite mock interview for you.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Virtual Onsite with Leon Wei for $1499

Career services by Leon Wei

7 services

Career planning is the most important thing to do for your career.

Whether you are looking to switch to a different career track, e.g., data scientist => product manager.

Or simply want to gain more visibility inside of your company, moving up the career ladder, you need an experienced mentor who had been there and done that.

Get practical advice on job search, career growth, pros n cons of different career paths to make the best decision.


“From an individual contributor to a senior manager running 20+ people org, I hope to share with you the lessons that I've learned so you can make the right choice, and avoid the same mistakes that I did.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Career advice with Leon Wei for $399

Data challenges or sometimes called take-home challenges are often sent to a candidate in the initial screening.

You are usually given a few tables with, generally speaking, open questions to demo your skills in the following area:

1. Basic data processing in R/Python or sometimes even SQL

Are you able to transform data before feeding them into a machine learning model?

For example: converting categorical variables into numerical columns; Handle missing values, what to do if there are missing values in specific columns. 

Spot obvious data errors based on logic or intuition, never assume the data is correct, fix it before use it.


2. Code quality

No one wants to review your code if you are hired and checked in poor quality code; 

Don't use crazy lambda functions combined with map-reduce and map to make yourself look smart. Instead, use long variable names that are meaningful, easier to understand.


3. Business and product sense 

Are you able to understand the business context? Do your conclusion and insights make business sense?


4. Clear communication

What is your conclusion, can everyone understand what you try to convey, and what do you recommend for the next steps.

You will often be asked to give a talk during the final round of interviews and answer the hiring team's questions.


5. Machine learning modeling skills

Can you build a classification model and evaluate its performance, what feature engineering steps worked the best, what are the metrics you used, did you run cross-validation to get an unbiased estimate of those metrics, etc.


6. Data visualization

One image is worth a thousand words, especially when you are constantly in meetings with non-technical people. Can you create an informative chart or graph to represent the data? Are you good with ggplot or seaborn?


Our mentors have conducted hundreds of take-home data challenges. Feel free to hire one and get 100% data challenge ready.


“I have given many take-home data challenges to candidates as a hiring manager.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Data Challenge with Leon Wei for $299

If you can't find exactly the service you are looking for: you can spend an hour with a mentor and asked their questions. 

How did you get where you are today?

Should I quit my job today?

Which area in machine learning should I be focused on? Image processing or natural language processing?

How to build a modern machine learning engineering team from scratch?

Anything you think our mentors can help you.


“General consulting, ask me anything.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ General consulting with Leon Wei for $499

If you would like to start a conversation but are not 100% convinced a mentor is right for you, this heavily discounted call (usually at 50% off) is here for you.

Use this opportunity to chat with your potential mentor and get to know each other.


“Let's get to know each other and make sure I would be the right mentor for you.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Introductory Call with Leon Wei for $199

If you are wondering if machine learning can help with your business use case, or wanted to utilize machine learning but not quite sure where to get started? Or wanted to switch to a machine learning career.

Why not spend some time and validate your idea from the world-class ML expert on instamentor.com?


“Most recently a senior manager of applied machine learning at  Apple, research scientist at Amazon, data science manager at Chegg. Expert in building large scale machine learning systems to solve business problems.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Machine Learning Consulting with Leon Wei for $399

The first impression matters a lot during your job search, and your resume delivers the first impression!

An HR person on average spends 10–15 seconds to go through your resume before he/she makes a decision. You want to make sure your resume looks and feels great and elegant.

Have an experienced mentor to analyze your resume and provide you valuable feedback.

When your resume is improved, you will get more job interviews, and more opportunities to land a dream job.

How it works

1. After you book a resume feedback session through Calendly, send the mentor a copy of your most recent resume;

2. The mentor will review your resume and save some notes on areas to be improved, and make some edits if necessary;

3. During the zoom call, the mentor will share their notes and suggestions, and share some tips and techniques that can help your resume catch a recruiter or a hiring manager’s eye;

4. After the meeting, you will rewrite your resume and send it back to the mentor;

5. The mentor will email back the final feedback and make necessary edits.


“I have seen thousands of resumes from hundreds of candidates in the last 10 years at tech companies such as Amazon. I will review your resume, help you improve it, so you can get more interviews.”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Resume feedback with Leon Wei for $299

Congratulations, you nailed your interview and received a job offer. Now what?

According to a report by salary.com, close to 50% of job applicants did not negotiate before they took their job offers.

Not negotiating leaves a significant amount of potential income on the table, which could be as high as one-two months of your base salary, can you imagine that?

And the #1 reasons for why not negotiating an offer is:

FEAR!

 

1. Afraid of losing the job offer

Which in reality, unless you messed up the negotiation, your future employer was expecting you to negotiate.

2. It is outside of your comfort zone

Many of us work on engineering or data-related roles, and if you are an introvert, it's tough for you even to start the conversation.

3. Information assymetry

You don't know how many offers they made to other candidates, the expected range of salaries for this role, etc.

 

But fear no more, because you will get help from an experienced mentor with

✅ A clear salary negotiation strategy.

We know industry standards have a deep understanding of the hiring process. We will first analyze your situations at this moment and help you better understand your leverage, strength, and weaknesses.

✅ Salary negotiation chat preparation

Jump on a call in a simulated salary negotiation process, rehearse salary negotiation with a hiring manager (kind of like a mock interview).

✅ Customized email scripts you can borrow 

Salary negotiation is a skill that takes years to be good at, and we have mentors who have been on both sides, years of hiring and interviewing experiences.

We will send you customized email scripts so you can easily respond in different situations.


“I have hired many candidates, also interviewed and negotiated many job offers for myself. I understand salary negotiation from both sides.,”


View Leon Wei's Calender and schedule a 1:1 meeting after your payment, securely processed by Stripe, fully refundable if canceled 24 hours before the meeting.

⏰ Salary Negotiation with Leon Wei for $399

👋 Hi there, for your convenience, here are my avails. However, you must first purchase a service before booking a time. Otherwise, the meeting will be canceled.