Staff Applied Scientist - Platform Core Analytics and Science at Uber (San Francisco, CA)

| San Francisco, CA
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About the Role
We are looking for a customer-centric Staff level Applied Scientist to join the Platform Core Analytics and Science (CAS) team!
You will help solve some of Uber's most challenging business goals, through high-profile work and inspiring thought leadership. You'll get to flex your statistical and machine learning models skills to tackle problems like travel time estimation, route optimization, search personalization and ranking, and experimentation design and analysis for new algorithm/feature/product launches. You'll work with leadership and multi-functional partners to solve broader data science problems, create data science vision, and guide the team's direction through data-driven insights and algorithmic thinking. Hopefully mentoring junior data scientists is your thing? If so, keep reading!
What You'll Do
  • Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimization, and work with engineering/product to productionize those algorithms and create impact in production.
  • Drive clarity and solve ambiguous, challenging business problems using data-driven approaches.
  • Work closely with multi-functional leads to develop technical vision and drive the team direction.
  • Propose and guide the framework of data analysis to drive business insight and facilitate decisions. Establish standard methodologies for data science including modeling, coding, analytics, and experimentation.
  • Provide technical mentorship for junior data scientists within and outside your team.
  • Communicate with senior management and multi-functional teams.
Basic Qualifications:
  • Minimum 5 years of industry experience.
  • M.S. or Ph.D. degree in Statistics, Machine Learning, Operations Research, or other quantitative fields. Alternatively, a BS with 5 or more years of experience in relevant fields.
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
  • Experience in experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
  • Experience in algorithm development and prototyping.
  • Coding proficiency, and ability to develop statistical analysis and prototype algorithms in Python.
  • Proficiency in SQL, R, Spark.
Preferred Qualifications
  • Tech lead experience is a plus
  • Experience with productionizing algorithms for real-time systems
  • Proficiency in Java
About the Team
Platform CAS is responsible for powering the core trip experiences externally and core decision making systems internally:
  • The mapping platform that performs travel time (ETA) prediction, route optimization, navigation, pickup & dropoff specification, and other geospatial technologies. These services are used throughout a trip cycle for both Rides and EATS, from key decision systems such as pricing and matching, and core trip experiences such as pickup, dropoff, and navigation experiences.
  • The Uber AI team that provides machine learning solutions to teams across the company, including designing and implementing algorithms, and building the machine learning platform that provides end-to-end capabilities for prototyping, data pipelining, training, serving, and monitoring in real-time. This team also serves the user location information, including GPS and sensor information, for use by various systems at Uber.
  • The Customer Obsession team that enables magical customer support experiences through in-app automation, experimentation, and NLP/chat-bot applications.
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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.

Silvia Penna

Sr Manager, Central Operations

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