Uber Data Analytics Interview Questions and Answers (2026 Guide)

Quick answer: Uber runs a genuine Data Science organisation out of Bangalore, with current listings for Data Scientist (Product Analytics), Data Scientist II and Staff Scientist roles all based there. Candidate-reported processes describe a 5-round Data Scientist loop covering a timed coding assessment, statistics and machine learning, experimental design, and behavioural and hiring-manager rounds, while a Senior Business Analyst account describes 4 rounds built around real Uber case studies, evaluating an Uber Eats city launch, sizing Uber's local ride share, and categorising drivers as good or bad on 4 metrics. Neither account states its interview city explicitly, so we flag that gap rather than assume it was Bangalore.

About Uber

Uber Technologies is the San Francisco-headquartered ride-hailing, food-delivery and freight company operating globally. Its Bangalore office runs a real Data Science function: current job listings include Data Scientist (Product Analytics), Data Scientist II, Staff Scientist and Scientist II roles based in Bangalore, alongside a Customer Obsession Data Science team that Uber describes as colocated with engineering, product and design there. (Uber Careers, Data Scientist (Product Analytics), Bangalore; Uber Careers, Data Scientist II, Bangalore)

Uber's Interview Process

• A detailed Data Scientist account on GeeksforGeeks describes 5 elimination rounds: a 2-hour online coding assessment on data manipulation, statistical analysis and algorithmic thinking; a 45-minute technical round on statistical models, hypothesis testing, regression, decision trees, random forests and gradient boosting; a 45-minute round on experimental design and A/B testing at scale, including statistical significance; a 30-minute behavioural round on teamwork and data-driven projects; and a 30-minute hiring-manager round on culture fit and career goals. (GeeksforGeeks, Uber Interview Experience for Data Scientist)

• A separate Senior Business Analyst account, the closest analytics-adjacent role with genuinely Uber-specific detail, describes 4 rounds: a technical round mixing SQL (subqueries, self-joins, pivot tables), Python and pandas questions with a business case, "How would you evaluate the success of Uber Eats when launched in a new city?"; a round with the guesstimate "Calculate the percentage share of Uber rides in your city" and a case on identifying KPIs to track Uber's growth in a new city within 3 months; a panel round with a case on categorising drivers as good or bad using 4 key metrics; and a final panel on stakeholder-conflict scenarios and a driver-retention case built around a "Rides/Hr" metric. (GeeksforGeeks, Uber Interview Experience for Senior Business Analyst)

• DataLemur lists real, named Uber SQL practice questions built on Uber-style schemas: computing the average "2nd ride delay" for riders who book their first ride the same day they sign up, and pulling each user's 3rd transaction with spend and date. (DataLemur, Uber SQL Interview Question; DataLemur, Uber SQL Interview Questions)

What Candidates Report

Across both GeeksforGeeks accounts, the recurring themes are SQL depth (joins, self-joins, subqueries, pivot tables, window functions), a genuine metrics-and-experimentation focus (A/B testing, statistical significance, choosing KPIs for a new-city launch), and business cases framed around Uber's actual marketplace: driver quality, driver retention, and evaluating a product launch like Uber Eats in a new city. This lines up with aggregator guides from InterviewQuery and Exponent, which describe SQL rounds using "trips, users, cities, and timestamps" schemas and a metrics round testing how candidates choose success metrics for a feature launch, though those guides are general process write-ups rather than sourced to a specific candidate. (Exponent, Uber Data Analyst Interview Guide)

What We Could Not Verify

Neither GeeksforGeeks account states the interview's city, so while GeeksforGeeks skews heavily toward Indian candidates and Uber's Bangalore office is independently confirmed to run real Data Science hiring, we cannot claim these specific rounds happened in Bangalore. Glassdoor's Uber Data Analyst and Data Scientist interview pages returned a 403 access error on direct fetch, so we have not repeated their aggregate difficulty ratings or percent-positive figures here, only what search-indexed summaries showed, which we are not treating as independently confirmed. We also found no verbatim, individually attributed take-home assignment text, only aggregator paraphrasing of what a take-home "often" covers.

How to Prepare

• Drill SQL on trip- and rider-style schemas: joins, self-joins, subqueries, pivot tables and window functions, since these are named directly in both the Data Scientist and Business Analyst accounts.

• Rehearse A/B testing and experimental-design fundamentals, including sample size and statistical significance, a confirmed 45-minute round for Data Scientist candidates.

• Practise marketplace-flavoured case studies and guesstimates, such as sizing a city's ride share or defining KPIs for a new-city product launch, since these are the genuinely Uber-specific questions we found, not generic case-interview templates.

• Prepare a driver- or rider-quality metric discussion, for example how you would define "good" versus "bad" driver performance, since this exact framing appears in a sourced candidate account.