Senior Data Scientist, Product - Rides, Eats, Grocery

Key Skills

Java Programming, Leadership, Python Programming, SQL, Machine learning techniques, Data science techniques, A/B Testing, Data Visualization, Looker, Tableau, R Programming, Data Engineering, Data pipelines, ETL frameworks, Mixpanel

Job Description

Are you interested in driving business and product strategy? What about using data to answer difficult questions and come up with interesting insights? If so, then this is the job for you! You'll get to use your quantitative skills, obsession and empathy towards customers and collaborative spirit to work closely with Product, Ops, Engineering, and Applied Scientists to provide data driven insights to find new opportunities to take our products to the next level.

As a Data Scientist in Uber's core analytics and sciences group, focused on Product Analytics, you'll work on:

• The analysis, manipulation, and visualization of data
• Establish data foundations for observability and monitoring through data engineering and ETL work
• Uncovering and communicating product or business insights and strategy
• Defining metrics and designing & analyzing experiments, such as a/b tests

Note on related roles:

While Data Scientists in this role may extend and apply machine learning or statistical models, if you're interested in a role focused on advanced modeling, please check out our Applied Science roles instead.

About the Teams

We are a key part of Uber's cross-functional product development teams, helping to drive every stage of product development through data analytic, statistical, and algorithmic expertise. Here are the teams that make it happen:

Eats & Grocery:

Data Scientists in Delivery (Eats & Grocery) work on Uber's ambitious and rapidly growing on-demand delivery business, which operates in more than 45 countries and is the largest delivery platform outside of China. Delivery is a 3-sided marketplace, comprising Eaters, Couriers, and Merchants (mostly Restaurants, but also Grocery, Pharmacy, Alcohol and others). Data Scientists solve many exciting problems across our consumer Eats app, merchant tooling, and marketplace automation.

Rides:

Data Scientists in Rides use data to improve and automate all aspects of Uber's core ridesharing products. For drivers, we are creating a seamless product experience across the driver journey: matching drivers to cars, smoothing onboarding onto our platform, and creating a stress-free trip experience. For Riders, we're building products that create an amazing experience from request to destination.

Platforms:

• Data Scientists in Platforms help develop the common systems and technical foundations that power Uber's customer experiences externally and core decision-making internally, including:

Maps:

• Data Scientists on Maps develop geospatial technologies that underlie Uber's systems-GPS location inference, travel time prediction, route recommendation, navigation, pickup & dropoff location setting and experience optimization, etc.

Uber for Business:

• The U4B team aims to bring the power of Uber to organizations, their employees, and their customers.

Experimentation:

• The XP platform at Uber supports novel experimentation designs and measurements for 2-sided and 3-sided marketplaces, powering company-wide experimentation for tens of thousands of experiments. XP is critical in providing reliable, trustworthy and agile experimentation enabling our business and product decisions.

What You'll Do

• Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of the data, our customers, and our business
• Design experiments and interpret the results to draw detailed and impactful conclusions.
• Define how our teams measure success, by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing
• Collaborate with applied scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
• Develop data-driven business insights and work with cross-functional partners to find opportunities and recommend prioritization of product, growth, and optimization initiatives.

Basic Qualifications

• Master's or Bachelor's degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative field. (If Master's degree, 1+ years of industry experience required; if Bachelor's degree, 2+ years of industry experience as a Data Scientist or equivalent)
• Advanced experience in at least one of SQL, Python, or R
• Basic understanding of experimental design (such as A/B experiments) and statistics fundamentals
• Experience in extracting insights from data and explaining their implications
• Experience with Excel and some dashboarding/data visualization (e.g., Tableau, Mixpanel, Looker, or similar)

Preferred Qualifications

• Advanced degree in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Machine Learning or other quantitative field
• 5+ years industry experience in consumer-facing data science
• 1+ years of experience providing technical leadership
• Strong storytelling: ability to distill interesting and hard-to-find insights into a compelling, concise data story
• Advanced experience with experimental design and statistical methods for causal inference.
• Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds
• Willingness to get your hands dirty with messy data to find opportunities and uncover insights