Lyft Business & Services Familiarity Questions

Familiarity with Lyft's business model, core products and services (ridesharing platform, mobility offerings, pricing strategy), partnerships, and market positioning as part of understanding the company's business and culture.

MediumTechnical

29 practiced

Compare near-real-time (streaming) analytics and batch analytics for a driver allocation dashboard. For each approach discuss latency, cost, complexity, accuracy, and examples of KPIs best suited for that approach. Recommend which to use for a driver rebalancing alert system and why.

HardTechnical

25 practiced

Corporate partnership billing is messy: riders sometimes use corporate credits, personal cards, or promo codes. Propose a robust attribution and reconciliation model that aligns ledger-level payments to trip events so partner invoices match actual trips. Describe data fields you'd rely on and reconciliation checks.

MediumTechnical

30 practiced

You want to measure the causal impact of a new loyalty program 'Lyft Rewards' on rider retention. Outline an experimental or quasi-experimental approach you would recommend, specifying treatment assignment, primary and guardrail metrics, sample size considerations, and how to handle contamination or eligibility changes mid-test.

HardTechnical

22 practiced

You have a slow, resource-heavy SQL query that joins trips (500M rows) with drivers and promotions to compute a rolling 7-day take rate per region. Explain concrete optimization steps: indexing/partitioning strategy, use of materialized or aggregate tables, rewriting SQL for incremental aggregation, and approximate strategies when exact accuracy isn't required.

EasyTechnical

30 practiced

You have the following table:

trips(trip_id bigint, rider_id bigint, driver_id bigint, start_time timestamp, end_time timestamp, status varchar)

Write a PostgreSQL query to compute weekly active riders (distinct riders per ISO week) for the last 12 weeks. Include week_start (ISO week start date) and war_count. Exclude cancelled trips and show weeks with zero as 0.

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