Data Scientist/Sr Data Scientist, Product Analytics - Core Services

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Core Services Data Science, Product Analytics, teams provide analytical insights and solutions for critical cross-company functions and processes that each affect how we show up in the world for our customers, including Safety + Insurance, Customer Focus, and Payments. As a Data Scientist in the Core Services organization, you get to use your quantitative skill set, 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 product and business to the next level

As a Data Scientist within Core Services Product Analytics, you'll focus on:

• The analysis, manipulation, and visualization of data
• Some data engineering/ETL (extract-transform-load) work
• Provide product or business insights and strategy
• You may also have an additional focus on the design and analysis of experiments, such as a/b tests

We've noticed that the title Data Scientist represents a variety of work across the industry. If you're more passionate about building machine learning (ML) or econometric models, please check out the Applied Scientist roles on our career page!

About the Teams

Safety and Insurance Data Science: The Safety and Insurance Data Science team provides insights and analytical solutions that are timely, accurate, and actionable to drive safety and deliver insurance. We partner closely with a highly cross-functional team including product management, engineering, operations, and policy teams to make the Uber platform as safe as possible through new products and policies

Customer Obsession Data Science: Building rich chat experiences in a variety of products for riders, drivers and eaters to help users solve their support needs with as little friction as possible.

Payments Data Science: Making meaningful contributions to our mission to streamline and optimize Uber's payment experience(s). On this team, you will shape the direction of Uber's payment experience by analyzing vast quantities of data to capture insights, identify opportunities, and ultimately prioritize product and engineering initiatives.

What You'll Do

• Refine ambiguous questions and generate new hypotheses about the product and business 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 data 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 identify opportunities and recommend prioritization of product, growth, and optimization initiatives.

Basic Qualifications

• M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields. (If M.S. degree, a minimum of 1+ years of industry experience required and if Bachelor's degree, a minimum of 2+ years of industry experience as a Data Scientist or equivalent)
• Experience in at least one scripting language (SQL, Python, or R preferred)
• Basic understanding of experimental design (such as A/B experiments) and statistical methods
• Willingness to get your hands dirty with messy data to identify product opportunities and uncover interesting product insights

Preferred Qualifications

• Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Machine Learning or other quantitative field
• 5+ years industry experience in consumer facing data science
• Strong storytelling: distill interesting and hard-to-find insights into a compelling, concise data story
• Advanced experience with experimental design and statistical methods such as causal Inference.
• Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds
• Strong judgment, critical-thinking, and decision-making skills
• Ability to solve complex business problems that cross multiple product/project areas and teams
• Balance attention to detail with swift execution