Data Scientist II - Uber for Business

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 Uber for Business (U4B) team strives to bring the power of Uber to Organizations, their Employees, and Customers. We are growing rapidly in a number of business areas and look to expand the Science team!

What you will Do

As a Data Scientist you will have the opportunities to work on exciting growth problems, build new products to cater use cases for business users, and improve product experiences. You will be responsible for:

• Identifying new opportunities and shaping the product roadmap through data insights.
• Guiding product development through experiments and deep dives.
• Build science solutions to critical business problems.
• Define and measure success for the whole team.

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 2+ years of industry experience required and if Bachelor's degree, 3+ years of proven experience as a Data Scientist or equivalent
• + proven experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar)
• Excellent SQL expertise.
• Solid understanding of experimental design (such as A/B experiments)
• Ability and experience in extracting insights from data, and summarizing learnings / takeaways
• Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar)

What You'll Need

• Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Machine Learning or other quantitative field
• 4+ years industry experience in consumer facing product analytics
• 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