Applied Science Manager - Platform Data Science at Uber (San Francisco, CA)

Uber

| San Francisco, CA

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About the Role
We are looking for a Tech Lead Manager to join the Platform Data and Applied Sciences team! Our team:

Develops geospatial technologies that underlie Uber's systems--GPS location inference, travel time prediction, route recommendation, navigation, pickup & dropoff location setting and experience optimization, etc.
Develops general machine learning approaches which are being applied in personalization and recommendation for various services at Uber.
Develops Experimentation design and measurement methodologies which powers the experimentation platform at Uber. This platform is critical in providing reliable, trustworthy and agile experimentation and experiment analysis to power business decisions across the entire Uber ecosystem
Maintains the core financial data and provides key business insights on core company-level KPIs such as revenue, profitability.

What You'll Do

Lead a team of applied scientists. Provide people management, technical and professional guidance for them. For example, lead the applied science team for the experimentation platform.
Work closely with leads from engineering and product to develop technical vision and drive the team direction.
Develop and build robust scalable solutions to business problems using algorithms based on machine learning and statistics.
Propose and guide framework of data analysis to drive business insight and facilitate decisions.
Communicate with senior management and cross-functional teams.

Basic Qualifications

Ph.D., MS or Bachelors degree in, Statistics, Economics, Machine Learning, Operations Research, Computer Science or other quantitative field. (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 required)
Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
Knowledge of experimental design and analysis
Experience with exploratory data analysis, statistical analysis and testing, and model development
Ability to use a language like Python or R to work efficiently at scale with large data sets
Proficiency in languages and tools like SQL, Hive, and Spark
Management experience

Preferred Qualifications

Minimum 3 years of industry experience.
Experience managing a team of applied scientists.
Ph.D. degree in Statistics, Economics / Econometrics, Machine Learning, Operations Research, or other quantitative disciplines.
Experience in experiment design and analysis and more generally causal inference.
Experience in algorithm development and prototyping.
Management experience: 2 years

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An Insider's view of Uber

What’s the vibe like in the office?

When I went into the office for my final interview with Uber, I had the same feeling that I did when I stepped onto my college’s campus for the first time: it just felt like the right fit. The office was high-paced but also relaxed and you could immediately tell that people were friends and genuinely enjoyed being there.

Paige Sammarco

Account Executive, Uber Eats

What kinds of technical challenges do you and your team face?

One of the big challenges today with experimentation is around guaranteeing correctness, especially for small changes to ensure confidence in results. Was that change the cause of new behavior? Did other experiments get in the way? It all comes down to how accurately you can detect small changes within consumer behavior.

Azarias Reda

Head of Uber's Experimentation API team

What makes someone successful on your team?

"It’s not just about the individual contributor. The most successful people are the ones learning from others. On my team, I make sure that everyone shares best practices and we foster a collaborative culture. So when you’re on a call, you’re never really alone. And that applies to everyone."

Ali Faivus

Head of Mid-Market Sales

How do you empower your team to be more creative?

We make sure we don’t ship org structures, but rather aligned products. How can our products complement one another, building upon each other to achieve our primary goals? Whether it’s scheduling, routing, predictive analytics, or operational excellence, we are acting as one, and smartly leveraging our domains and strengths.

Joe Chang

Director of Engineering, Uber Freight

How does your team reward individual success?

I believe recognizing someone’s contributions are a big part of team play. On our weekly meetings, we always start with a shout-out, and it’s amazing how this simple topic stimulates the team to recognize small victories and accredit colleagues for their accomplishments. This brings our team together and fosters a more collaborative environment.