At (COMPANY NAME), 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 (COMPANY NAME)'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 (COMPANY NAME) 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 (COMPANY NAME)'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:
* Advanced Technologies for Detecting and Preventing Fraud at (COMPANY NAME)
Read full job description
Source:
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About (COMPANY NAME)
At (COMPANY NAME), 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.
We're looking for PhD intern candidates to join the Research and Economics team in Summer 2019 (3 months). We seek candidates with a strong background in economics, transportation research, or other quantitative social sciences. Depending on your background and interests, you could focus your work in one of two areas:
* Economics: Conduct research to understand our business and driver-partners in the context of the economies in which (COMPANY NAME) operates. For example: We know that the flexible work model is very valuable to (COMPANY NAME) drivers (see Chen et al., Angrist et al.) and that dynamic pricing is vital in protecting the health and efficiency of the dispatch market (see Castillo et al., Surge Pricing Solves the Wild Goose Chase); however, it's likely that consistency (e.g., of pricing or earnings) also carries some value for riders and drivers. What values should we put on these opposing virtues?
* Cities and Urban Mobility: Study (COMPANY NAME)'s impact on riders and cities around the world with a special focus on different facets of urban mobility. For example: What is the relationship between on-demand transportation and existing public transport systems. Do they complement or compete with each other? Or, does this relationship change depending on external factors? What could these external factors be and how do they change rider behavior?
What You'll Do
* Conduct rigorous, careful statistical and econometric analysis in support of our research priorities
* Develop assets (maps, visuals etc.) that explain our research for policy and communications needs
* Manage relationships with outside academics and research partners to ensure research collaborations run smoothly
* Communicate cross-functionally to understand the intersection of policy, product, legal, and operations and develop research that informs business or policy decisions
* Present your results internally and externally; in some cases, writing academic papers with great researchers from top universities
What You'll Need
* PhD student (anticipated graduation in 2020) in Economics, Statistics, Public Policy, or other quantitative social science.
* 2 years of quantitative research or data science experience
* Strong data skills and the ability to learn to use tools such as SQL, Python, R, and GIS mapping tools to work efficiently at scale
* The capacity to work independently and execute a research plan with minimal oversight
* The ability to organize and synthesize analyses and communicate data insights with clarity
* Enthusiasm for learning and growth
About the Team
The Research and Economics team, led by the Chief Economist, is responsible for addressing the thorny policy and business challenges impacting (COMPANY NAME) globally. As a data scientist on this team, you would be expected to bring analytical and empirical rigor to bear on important questions relating to economics, transportation policy, and urban planning.
Read full job description
Source:
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