Data Science Manager, Trust & Safety

  • Creditkarma
  • San Francisco, CA
  • Jan 14, 2020
Engineering

Job Description

Data Science Manager, Trust & Safety

Credit Karma is a mission-driven company, focused on championing financial progress for our more than 100 million members in the U.S., Canada and U.K.  While we're best known for pioneering free credit scores, our members turn to us for tips as they work on their  financial goals, including helping them monitor their credit, identity monitoring, searching for credit cards, shopping for loans (car, home and personal), filing their taxes with Credit Karma Tax and growing their savings* -- all for free. Credit Karma has grown significantly through the years: we've added more than 70 million members in the last five years alone and now have more than 1,100 employees across our offices in San Francisco, Charlotte, Los Angeles, Leeds, London and soon Oakland.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. *Banking services provided by MVB Bank, Inc., Member FDIC

What the Job Entails:

  • Manage a team focused on protecting Credit Karma members
  • Hands-on approach.  You'll be designing and implementing fraud systems, models and technology.  
  • Leading, controlling, and measuring performance of strategies to control fraud, enhance account security, achieve enterprise fraud and KPI goals.
  • Makes sure OKRs are hit with quality
  • Communicate clearly and concisely in high stress situations. 

Our Ideal Candidate:

  • Knows how to hire, grow, and retain technical talent
  • Has strong data query, analytic and modeling skills
  • Follows emerging technologies with a passion and becomes expert with them.
  • Strong organizational and process management skills
  • Demonstrated ability to manage staff to meet deadlines, complete important time sensitive tasks & adapt quickly to last minute changes.
  • Established networks with regulatory and industry organizations.
  • Over ten years of experience in a security, fraud, identity or a related area
  • At least three years experience managing high performance teams
  • Leadership skills and has remained hands on technical.
  • Expert knowledge of Python (or R or SAS), and SQL, or similar industry standard tools used for large-scale data analysis and modeling
  • Experience and/or interest in latest machine learning techniques (Random Forest, Gradient Boosting Trees, Deep Learning) and tools (SciKit-Learn, Hadoop, Hive, etc) strongly preferred