Quick summary
Summarize this blog with AI
Lyft data scientist interview case study from a recent instamentor student.
Overall it took 5 weeks.
TLDR
Candidate: N/A
How it gets started: Recruiter reached out on LinkedIn
Job level: T5
Year of Experience: 5–10
Degree: M.S & B.S. in CS
Offer: Yes
TC: ~450K USD
Location: San Francisco
Interview process: 5 weeks
Preparation: 2 months
Has a job: yes
Decide to join: N/A
Round 1: HR call
Why are you interested in Lyft, why do you wanna leave your current job, are you willing to relocate to San Francisco (in the city, where the HQ is based)
Round 2: Statistics & Probability & metrics
Fellow data scientist from the team gave a call and deep dive into the resume and focus on technical knowledge.
How do you choose the right metrics to evaluate the healthy of Lyft's carpool service?
How do we know if we are performing well/poorly in this newly expanded city?
Round 3: Take-home data challenge
Given the existing A/B testing data, how can we improve the cancellation policy? What is your conclusion?
3 datasets: control + treatment 1 + treatment 2
Asked to submit a keynote presentation
Round 4: virtual onsite/final round
SQL: window functions, rank, lag/lead
Leadership/Behavioral questions. Tell me about a time you take a lead and go far and beyond for your customer. How do you influence others without being the manager?
Product case study: how to evaluate customer experience, what metrics to use, how to improve.
A/B testing. What if p-value is > 5%
Presentation. Based on the submitted homework, what is your conclusion, what should we do, anything actionable based on the data?
Final Offer
Total about 450k,
~210k base salary
~220k from RSU (4-year vesting, total grant = 900k)
~25k sign-on bonus
