Risk Data Science and Analytics teams provide insights and develop machine learning models and strategies to combat payment fraud and marketplace abuse, improve account security and integrity, and minimize credit risk for financial products.
About The Role
They’re looking for a Risk Strategy Analyst to join the team to apply a data-driven approach to identify, understand, and scope emerging fraud trends (including payment fraud and marketplace risk) on the Uber platform. In this role, you’ll be part of and work closely with a cross-functional team consisting of engineers, product managers, operations, data scientists, and other analysts. You will require a mix of business and technical acumen, along with cross-functional skills to connect with various internal and external partners.
What You’ll Do
- Perform 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 a deep understanding of the Risk data, reporting, and key metrics
- Participate in project definition and idea generation, work on collaborative projects with partners across the globe with a focus on the Risk/Fraud mitigation
- Effectively communicate and present findings to the management team to strengthen business decisions
- With guidance from the manager, define and develop an 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
Basic Qualifications
- Minimum 1 year of experience in a data-focused role such as product analytics, business analytics, business operations, or data science
- Advanced degree in Mathematics, Statistics, Computer Science, Economics or another quantitative field
- Experience with data analysis and visualization tools, such as Python, R, Tableau
- Proficient at defining, utilizing, and communicating performance metrics
- Proven track record of applying analytical/statistical methods to tackle real-world problems using big data
Preferred Qualifications
- 3+ years of experience in a data-focused role such as product analytics, business analytics, business operations, or data science
- Risk/Fraud/Payments experience
- 3+ years of SQL experience
- Prior work with Hive, Spark, and other big data tools
- Experience in experimentation, A/B testing, and statistical modeling a plus
- Python/R
- Creative problem solving, strong critical thinking, and a get things done mentality
- Hands-on and attentive to detail
- Comfort with ambiguity and the ability to work in a self-guided manner
- Passion for Uber!
