Target · Lead Product Analyst

Analytics — SQL + Python + case studies, rejected

Bengaluru · Feb 2026 · 2 views

Rejected

7 yrs exp·Tier-2·Product startup·Recruiter outreach

Total process: 15 days

4 rounds: →→→

Background

I have 6–7 years of experience, working at a product company at the time. I'm from a tier-2 college, and I interviewed for a Lead Product Analyst role on Target's Analytics team in Bengaluru.

How I Got the Interview

A recruiter approached me directly, and I got a first response within about 2 days. I prepped for roughly 3–4 weeks before the rounds started.

Timeline

When	Stage
First week Feb 2026	HR intro call · ~20 min · cleared
After 2–3 days	Round 1 — Technical (SQL + Python) · ~1 hr · cleared
After 5 days	Round 2 — Case study / ML · >1 hr · cleared
After 5 days	Round 3 — Hiring Manager · ~40 min
After ~1 week	Decision — did not make it

Rounds

Round 1 — HR Intro Call

Format: Call | Duration: ~20 min

This was a discussion about the role and expectations. She mentioned the role involves collaborating cross-team with Design and Engineering, and that I'd be leading 2–3 people.

Prep guidance for upcoming rounds

3 rounds total: 1 Technical, 1 Case study/ML, 1 HR Manager round
Final salary discussion after the rounds

Verdict: Cleared

Round 2 — Technical

Format: Video | Duration: ~1 hr (took the full hour)

Started with a 3-minute introduction. The core of this round was SQL and Python — for each question I was asked to solve it in both SQL and Python.

SQL & Python

Easy SQL warm-ups: RANK, DENSE_RANK, etc. — then the same in Python
A couple of medium questions in both SQL and Python
Python basics on data handling: sorting, filtering, grouping

Q1 — For an Uber driver dropping people off, find the areas where the driver had the least distance before getting the next ride (solve in Python and SQL).

rides

column	type
ride_id	INT (PK)
driver_id	INT
dropoff_area	VARCHAR
dropoff_lat	DECIMAL
dropoff_lng	DECIMAL
pickup_lat	DECIMAL
pickup_lng	DECIMAL
pickup_time	TIMESTAMP
dropoff_time	TIMESTAMP

Q2 — A customer visited multiple places; figure out how many of the rides were closed-loop (e.g. A→B→C→D→A, closed and without breaks).

Hint: use lead/lag.

trips

column	type
trip_id	INT (PK)
customer_id	INT
source	VARCHAR
destination	VARCHAR
trip_time	TIMESTAMP

Verdict: Cleared

Round 3 — Case Study / ML

Format: Video | Duration: >1 hr (ran over the scheduled hour) | Interviewer: Lead Analyst

Started by going through my resume and discussing my projects.

Q1 — Guesstimate: how many people in Bangalore order food online?

Q2 — If there is a drop in sales, how would you perform the RCA?

Q3 — ML questions based on my resume: why did you use Random Forest, and what are its advantages?

Why you used a certain model
What is recall
What is precision

Verdict: Cleared

Round 4 — Hiring Manager

Format: Video | Duration: ~40 min (scheduled for 1 hr) | Interviewer: Hiring Manager

This was a behavioural and experience-focused conversation.

Q1 — Tell me about your projects and CV.

Q2 — Do you have experience leading teams?

Q3 — Explain a project where you collaborated with different teams.

Q4 — Walk me through pricing-related use cases and projects.

Q5 — How do you handle stakeholders with conflicting ideas?

Verdict: Rejected

Final Outcome

I reached out to HR after 2–3 days and heard back after about a week — it was a negative response, and I did not make it.

Tips for Future Candidates

Be ready to solve the same problem in both SQL and Python in the technical round — every question was asked in both.
Expect window-function-heavy SQL (rank/dense_rank, lead/lag) framed as real-world case studies like ride/trip data.
For the manager round, prepare concrete stories on team leadership, cross-team collaboration, and stakeholder management with conflicting priorities.