Data Science II, InsurTech

About the Role

We're looking for a data scientist to join our InsurTech Data Science team under Core Services to provide data expertise as we work to make this world a safer place to move around.

This is a cross-functional role within a global team that will work closely with product management, safety operations, engineering, and partner data teams. The work has a global scope, with different cultural and regional aspects considered for each of the studies.

Uber's Stand for Safety value shows the importance and relevance of Safety here:

"We embed safety into everything we do. Our relentless pursuit to make Uber safer for everyone using our platform will continue to make us the industry leader for safety. We know the work of safety never stops, yet we can and will challenge ourselves to always be better for the communities we serve."

What the Candidate Will Need

---- What the Candidate Will Do ----

The InsurTech Science team applies data science and analytics to insurance initiatives from delivering the best auto crash reporting experience to ensuring the most accurate claims handling process. As a member of the team you will conduct deep-dive analyses, design and analyze experiments, lead projects end-to-end, and support the development of machine learning models to make our platform as safe as possible for all users. You will play an influential role in driving critical products and policy decisions.

---- Basic Qualifications ----

1. M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields
2. Advanced proficiency in SQL
3. Proficiency with Python or R
4. Familiarity with experimental design (e.g., A/B experiments) and statistical methods
5. Experience with dashboarding and data visualization tools such as Tableau, Looker or similar

---- Preferred Qualifications ----

1. Exceptional judgment, critical-thinking, and decision-making skills
2. Advanced degree or similar in Mathematics, Statistics, Computer Science, Economics
3. Ability and experience in extracting insights from data, and summarizing findings / takeaways
4. End to end experience with product analytics and experimentation
5. 4+ years of Python or R experience
6. 4+ years of SQL experience
7. Experience with Data Pipeline/ETL creation
8. Ability to identify stakeholders, build relationships, and influence others to get work done
9. Strong ability to document research and analysis

For San Francisco, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year.

For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link .

Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form .

Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.