Director, Data Science Trust & Safety

  • People Management
  • Oakland, CA, USA
  • Experience level: 10+ years

Credit Karma

This content was reproduced from the employer’s website on June 21, 2021. Please visit their website below for the most up-to-date information about this position.

Credit Karma depends upon our users’ trust.  We earn and maintain that trust by demonstrating our commitment to safeguarding their information.  The Trust & Safety team has the critical responsibility of protecting Credit Karma’s members by securing our online processes and preventing online fraud and abuse throughout the Credit Karma product suite.  Credit Karma’s Trust & Safety team is looking for a Director of Trust & Safety Data Science to lead all our efforts related to building machine learning models to protect our members.  

What you’ll do:

  • Manage a team of data scientists focused on protecting Credit Karma members
  • Design and implement fraud models and technology 
  • Leading, controlling, and measuring performance of strategies to control fraud, enhance account security, achieve enterprise fraud and KPI goals
  • Build a strategic roadmap for data science model development in Trust & Safety
  • Own the entire lifecycle of fraud model development

What’s great about the role:

  • Build the future of fraud prevention technologies to protect our members 
  • Scale the team as we continue to grow 

Minimum Basic Requirement:

  • Experience in developing machine learning models in an adversarial environment (such as fraud or abuse prevention)
  • Expert knowledge of Python (or R or SAS), and SQL, or similar industry standard tools used for large-scale data analysis and modeling
  • Experience in machine learning techniques (Random Forest, Gradient Boosting Trees, Deep Learning) and tools (SciKit-Learn, Hadoop, Hive, etc) 
  • 5+ years of experience in managing data science teams
  • 10+ years of experience in security, fraud, risk or a related area
  • BA/BS degree in relevant major or equivalent practical experience, preferable in Computer Science, Statistics, Mathematics or an equivalent discipline.  Postgraduate degree preferred

Preferred Qualifications: 

  • Knows how to hire, grow, and retain technical talent
  • Able to guide team in model development (eg. should a model developer choose xgboost or random forest; how to reduce model overfitting)
  • Follows emerging technologies with a passion and becomes expert with them
  • Demonstrated ability to manage staff to meet deadlines, complete important time sensitive tasks & adapt quickly to last minute changes
  • Over ten years of experience in a security, fraud, identity or a related area
  • Experience in productionalizing and optimizing machine learning models in environments requiring very fast response

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