Data Science Manager, Payments Fraud

Uber Overview

About Uber

Uber is a technology company that is changing the way the world thinks about transportation. We are building technology people use everyday. Whether it's heading home from work, getting a meal delivered from a favorite restaurant, or a way to earn extra income, Uber is becoming part of the fabric of daily life.

We're making cities safer, smarter, and more connected. And we're doing it at a global scale-energizing local economies and bringing opportunity to millions of people around the world.

Uber's positive impact is tangible in the communities we operate in, and that drives us to keep moving forward.

Job Description

We are building a world class team that uses machine learning to execute Uber's vision of transportation as reliable as running water. We are looking for an experienced machine learning leader to build the team responsible for payments fraud models across all Uber business lines (Rides, Eats, Freight, etc), all global regions and across multiple payment schemes (Credit Cards, PayTM, Paypal, cash, etc). This role will also lead the development of the first machine learning models for customer appeasements, a huge efficiency opportunity for Uber.

You will work together with the product management, engineering and strategy leadership and will have direct exposure to Uber's executive team. The machine learning models your team creates will be a key pillar supporting Uber's exponential business growth and real time transactions. Your team will leverage Uber's leading machine learning infrastructure with the world's richest dataset about how people move. The team also benefits from Uber's unique talent pool spanning several machine learning domains, including our advance research groups and the Uber AI labs (formerly Geometric Intelligence), applying and extending their research to our domain areas. As a leader of the Payments Fraud Data Science team, you'll be instrumental in hiring and mentoring the top data scientist and machine learning talent in the industry.

What you'll need

  • An inclusive team spirit: you thrive in diverse teams and everyone in the team loves working with you.
  • At least 5 years experience managing and at least 3 years experience as an individual technical contributor within data science or machine learning. Different role levels are available depending on the candidate experience and performance.
  • Ability to identify opportunities and lead/grow data scientists through efficient execution.
  • You must be persuasive, patient, compassionate and possess exquisite prioritization skills.
  • Biased toward action. You must be able be able to do more with less and turn would be blockers into opportunities for growth.
  • Excellent execution, organization and ability to collaborate. To be successful in this role, you should be comfortable executing with little oversight and be able to adapt to problems quickly.
  • Strategic mindset. You're comfortable thinking a few steps ahead of where the team is at now.
  • Hands on mastery of data wrangling, modeling, and telling a story based on data
  • A strong background in mathematics, statistics, machine learning combined with experience using these skills to solve hard problems
  • A natural desire to learn and innovate: ML and Risk are fast-paced domains and we need to find the most efficient and clever approaches to solving risk problems
  • Experience working in payments fraud or credit risk modeling is desired but not mandatory
  • Knowledge of the latest ML techniques like deep learning is a plus, but not a requirement

Perks

Perks

  • Employees are given Uber credits every month.
  • The rare opportunity to change the way the world moves. We're not just another social web app, we're moving real people and assets and reinventing transportation and logistics globally.
  • Smart, engaged co-workers.

Benefits

  • 401(k) plan, gym reimbursement, nine paid company holidays.
  • Full medical/dental/vision package to fit your needs.
  • Unlimited vacation policy; take time when you need it.

Be sure to check out the Uber Engineering Blog to learn more about the team.

Uber is an equal opportunity employer and enthusiastically encourages people from a wide variety of backgrounds and experiences to apply. Uber does not discriminate on the basis of race, color, religion, sex (including pregnancy), gender, national origin, citizenship, age, mental or physical disability, veteran status, marital status, sexual orientation or any other basis prohibited by law.


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