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2019 PhD Data Scientist Internship - Risk

San Francisco, CA,Data Science, University

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.

 

We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.

About the Role 

 

We’re looking for PhD intern candidates to contribute to Risk data science in Summer 2019 (3 months) in our San Francisco and Palo Alto locations.  We seek candidates with strong background in statistics, machine learning, computer science, and operations research. You will be embedded in a cross-functional team such as Payment Risk, and work closely with the engineers, risk analysts, and product managers under the supervision of a data scientist in that team. You’ll be focused on modeling and algorithm development on a project defined by you and your mentor.  

What You'll Do

 

  • Work with your mentor closely to scope a project, define the problem, and develop and prototype the solution
  • Work alongside engineers, risk analysts and product managers to understand the business use cases and production feasibility of your work, and collaborate on the experimentation and productionisation of your work
  • Develop creative solutions to product problems using advanced mathematical algorithms such as machine learning and optimization
  • Communicate with senior management and cross-functional teams

 

Sample Projects

 

  • Develop machine learning models to detect payment fraud and marketplace abuse on Uber’s platform
  • Develop innovative features that leverage new sensor data and improve model performance
  • Develop NLP and computer vision models for user experience improvement
  • Develop graph based features and machine learning models to identify bad actors

 

What You’ll Need

 

  • Ph.D. student (anticipated graduation in 2020) majoring in Computer Science, Statistics, Operations Research, or any other quantitative disciplines
  • Experience in modeling and algorithm development
  • Coding proficiency and the ability to develop statistical analysis and prototype algorithms in Python or R.  Proficiency in Java is a plus
  • Ability to communicate effectively with both technical and business stakeholders

 

About the Team

 

The Risk Data Science team develops machine learning models to support multiple Uber business lines (Rides, Eats, U4B, etc). We are responsible for identifying bad actors while providing magical experiences to good riders and drivers. Our team works together with product managers, engineers, and risk analysts.

As a member of our team, you'll protect Uber's riders and drivers by bringing state of the art technology to bear on the world's richest dataset about how people move. You will experiment with a range of machine learning techniques including supervised, unsupervised and active learning approaches (e.g., tree-based models, CNN, LSTM, and DBSCAN), and tackle a variety of interesting and challenging problems including computer vision, NLP, knowledge graph, identity and reputation scores, mobile sensor and GPS feature development.

 

You can learn more about us through this blog post:


歡迎參閱我們的求職者私隱聲明

Uber 不但接納並尊重和支持個人差異,致力為我們的員工、產品和社會帶來莫大益處。Uber 以實際行動積極提供公平公正、人人平等的工作環境,並對此引以為傲。我們承諾提供平等的就業機會,不論種族、膚色、祖籍、宗教、性別、出生國家、性取向、年齡、國籍、婚姻狀況、殘障、性別認同或退役狀況。