Here is what a Walmart Data Scientist Interview process may look like:
TLDR
Candidate: Jonny
Group: personalization & recommendation
How it gets started: a friend did an internal referral
Job level: X5
Year of Experience: 5 - 10
Degree: M.S & B.S. in CS
Offer: Yes
TC: ~350K USD
Location: Sunnyvale, CA
Interview process: 4 weeks
Preparation: 2 months
Has a job: yes
Decide to join: N/A
Technical screen round 1:
Basic Python and SQL coding problem
Case study: given a customer's shopping history, predict the next product they will buy.
Technical screen round 2:
Resume deep dive
Case study: predict user's gender given a user's shopping history, names, geo-locations, etc.
Coding: given a set of web pages, implement TF-IDF for a keyword for every webpage.
Virtual Onsite:
Round 1: Machine Learning Concepts
a. How to prevent over-fitting
b. Explain bias vs. variance tradeoff
c. random forest vs. gradient boosted trees, pros and cons
d. How to handle unbalanced samples
Round 2: Coding
Python: kth largest element in an unsorted array
SQL: session stitching
Round 3: ML modeling
Build an ML model to identify users who might be interested in buying product A, what features to use, how to handle categorical variables.
Which algorithm to use, and how to evaluate its performance.
Round 4. Data Modeling
Design a database, ETL jobs, batch processing with Spark
Round 5. Behavioral questions
Leadership, how do you handle deadlines, conflicts with coworkers.
Offer
Received a verbal offer the following week.
