The Analytics team is looking for a data scientist to guide measurement, strategy, and tactical decision-making for the larger Fraud & Risk team at DoorDash. Data Scientists on Fraud Analytics work closely with Engineering and Operations to identify new and emerging areas of fraud, diagnose patterns, and build new methodologies to accurately detect and prevent potential fraud while being mindful of the user experience.
About The Role
As a Senior Data Scientist supporting Fraud and Risk at DoorDash, you’ll use your quantitative background to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. You will take ownership of multiple Fraud areas and partner with their Engineering and Operations teams to design solutions to prevent fraudulent behavior, ranging from complex business rules to machine learning models.
In addition to driving advanced analysis and experimentation, you will mentor other data scientists and contribute to the high-level strategy and roadmap of Fraud and Risk prevention at DoorDash. They tackle many exciting challenges given the highly dynamic nature of fraudulent behavior. If you enjoy finding patterns amidst the chaos, and have experience using analytics to promote fraud and risk strategy, they’re looking for someone like you!
You’re excited about this opportunity because you will…
- Will analyze rich user and transaction data to surface patterns, trends, and bugs using SQL, R, or Python on our anti-fraud risk engine
- Create experimentation on new methods and build new models to predict fraudulent behavior
- Produce recommendations and use statistical techniques and hypothesis testing to validate your findings.
- Assess the effectiveness of existing fraud models, and enhance our solutions where necessary
- Partner with engineering, product, and operations teams to monitor fraud risk strategies and improve the roadmap.
- Manage the reporting of findings to management to steer the Fraud team’s strategic vision
- Work backward from understanding and sizing problems to ideating solutions
- Mentor junior analysts on how to use more advanced methods and solve challenges
They’re Excited About You Because…
- A degree in Math, Physics, Statistics, Economics, Computer Science, or similar domain
- 4+ years in a data science role working on fraud and risk systems
- A high level of expertise using fraud patterns and analytics to identify insights and create a response plan
- Deep expertise with SQL queries, ETL, and statistical analysis (e.g. hypothesis testing, experimentation, regressions) with statistical packages, such as R or Python
- Experience with multivariable modeling
- Proficiency in one or more analytics & visualization tools (e.g. Chartio, Looker, Tableau)
- Seasoned ability with managing timelines, delivery, requirements, and communication to internal partners and senior management to achieve lofty goals
- The insight to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
- The determination to initiate and lead projects to completion in a scrappy environment
DoorDash is a technology company that connects customers with their favorite local and national businesses in over 4,000 cities and all 50 states across the United States and Canada. Founded in 2013, DoorDash empowers merchants to grow their businesses by offering on-demand delivery, data-driven insights, and better in-store efficiency, providing delightful experiences from door to door. By building the last-mile delivery infrastructure for local cities, DoorDash is bringing communities closer, one doorstep at a time. Read more on the DoorDash blog or at www.doordash.com.
Their Commitment to Diversity and Inclusion
They’re committed to growing and empowering a more inclusive community within their company, industry, and cities. That’s why they hire and cultivate diverse teams of the best and brightest from all backgrounds, experiences, and perspectives. They believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Job ID #1100177
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1