DoorDash is hiring a

Manager, Fraud & Risk Analytics

San Francisco, United States

The Analytics team is looking for a Manager to drive measurement and identify opportunities for improving our fraud practices across our three audiences - Consumers, Dashers and Merchants.  You’ll take ownership over multiple discrete fraud segments to develop and execute a strategy which addresses fraud in the earliest stages of detection. You’ll define fraud prevention measures that are mindful of the impact on good user experience while inhibiting fraudster’s ability to reach our platform.

The team is fast-paced, high-energy, and meticulous in diagnosing emerging fraud patterns and preventing fraud loss before it can happen. We conduct rigorous analysis of complex data sets, set up multiple layers of business rules, models, and other processes to prevent potential fraud. We are a highly cross-functional team and regularly engage in discussion and reviews with stakeholders to prioritize plans for reducing fraud impact and introducing safety features.

We are looking for a Manager to work alongside a team of data analysts, engineers and operations specialists to analyze, investigate and identify solutions to prevent and mitigate fraud. You’ll be responsible for proactively identifying fraud patterns and sources to minimize the company’s exposure to financial and reputational risk. The ideal candidate has a high level of subject matter expertise and is experienced in utilizing information generated from fraud patterns, data analytics and business knowledge to identify insights and formulate a response plan.

What You’ll Do

  • Analyze the effectiveness of existing fraud models and oversee the design, development, and management of new real-time fraud rules and models
  • Develop, augment and validate fraud identification and prevention solutions and processes and ensure appropriate cross-functional support to deal with systematic and malicious fraud events
  • Partner with Engineering, Product and Operations teams to conceive, design & monitor fraud risk strategies in order to mitigate fraud risk in the most precise manner possible
  • Manage the reporting of key performance indicators; present analyses and findings to management to steer the Fraud team’s strategic vision
  • Work with the business and product teams to develop, implement and maintain effective risk management programs to align with the business needs
    • Identify and quantify levers to help move key metrics
    • Recommend which product features to build and why
  • Analyze rich user and transaction data to surface patterns, trends, and bugs that help inform our fraud policies and processes and contribute to our anti-fraud risk engine
    • Performing analytical deep-dives to identify problems, opportunities and actions required;
    • Collecting, processing, and cleaning data from disparate sources using SQL, R, Python, or other scripting and statistical tools; and
    • Perform ad hoc data analysis to remove roadblocks and ensure operations and automation are running smoothly

About You

  • High-energy and confident - you’ll do whatever it takes to win
  • Detail Oriented - you do your due diligence when completing a task whether it’s one-off analysis, an ongoing investigation, or a broader project
  • Get-it-done mindset. You’re not afraid of long hours, able to handle stress well, humble and scrappy!
  • Adaptable, resilient, and able to thrive in ambiguity - things change quickly in our fast-paced startup and you’ll need to be able to keep up!
  • Growth-minded - you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
  • Desire for impact - ready to take on a lot of responsibility and work collaboratively with your team

Qualifications

  • 3-5 years of applicable experience in a data analytics, consulting, or other quantitative role
  • An ability to write very complex SQL queries.  ETL experience a plus
  • Proficiency in one or more analytics & visualization tools  (e.g. Tableau, Chartio, Looker)
  • A deep understanding of statistical analysis (e.g. hypothesis testing, experimentation, regressions) and familiarity with statistical packages, such as Matlab, R, SAS or Python
  • Strong business judgment. You've got the ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
  • Bachelor's Degree in Math, Physics, Statistics, Economics, Computer Science, or other quantitative field

About Us

Founded in 2013, DoorDash is a San Francisco-based technology company passionate about transforming local businesses and dedicated to enabling new ways of working, earning, and living. Today, DoorDash connects customers with their favorite local and national restaurants in more than 1,000 cities across the United States and Canada. By building intelligent, last-mile delivery technology for local cities, DoorDash aims to connect people with the things they care about — one dash at a time.

 

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