Data Scientist / Data Analyst, Safety

Key Skills

Finance, Java Programming, Looker, Microsoft-Excel, Mixpanel, Python Programming, R Programming, SQL, Tableau

Job Description

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.

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 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 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

• 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)
• Advanced SQL expertise
• Basic understanding of experimental design (such as A/B experiments) and statistical methods
• Ability and experience in extracting insights from data, and summarizing findings / takeaways
• Experience with Python, Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar)

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 handle relationships with partners coming from both technical and non-technical backgrounds
• Experience with analytics of machine learning-based products a plus