Data Scientist, Risk

Uber is hiring for the role of Data Scientist, Risk!

Responsibilities of the Candidate:

• Perform statistical analysis to understand Risk / Fraud behaviors, contribute to fraud detection features and models;
• Build and maintain fraud rules in response to evolving fraud behaviors;
• Extract insights from the large volumes of data and come up with new strategies to mitigate/stop fraudulent activities;
• Build deep understanding of the Risk data, reporting, and key metrics;
• Conduct experimentations to test and optimize the effectiveness of risk mitigation solutions and products.
• Participate in project definition and idea generation, work on collaborative projects with stakeholders across the globe such as product, engineering, comm ops and data science with a focus on the Risk/Fraud mitigation;
• Effectively communicate and present findings to the management team to strengthen business decisions.
• With guidance from manager, define and develop area of expertise;
• Attend regular training courses, functional business review meetings, and all-hands;
• Stay highly engaged and always hustle as Uber Risk is a very fast-paced environment

Requirements:

• Minimum 1 years of experience in a data-focused role such as product analytics, business analytics, business operations, or data science
• Bachelors or Masters in Mathematics, Statistics, Computer Science, Operational Research, Economics or other quantitative field.
• Proven track record of applying analytical/statistical methods to solve real-world problems using big data.
• Creative problem-solving, critical thinking skills, and get things-done attitude.
• Advanced SQL expertise.
• Experience using Python.
• 1yrs+ experience in improving products, understanding the user journey, and extracting insights from data.
• Understanding of experimental design and using statistical methods in exploratory analysis.
• Experience with dashboarding/data visualization (i.e. Google Data Studio, Tableau, Mixpanel, Looker or similar).
• Comfort with ambiguity and the ability to work in a self-guided manner
• Superb communication and stakeholder management skills
• Proven aptitude toward Data Storytelling and Root Cause Analysis using data