Risk Data Scientist
Bread makes essential purchases affordable to regular people. We transform pricing in e-commerce: The $1,000 couch you’re looking at might become a $50/month charge. We treat our customers with dignity with clear and transparent products.
To enable this vision, we have enormous and engaging risk and data science challenges. We instantaneously approve and price credit products, predict fraud and customer’s propensity and preferences using predictive tools and logical criteria while providing a seamless and frictionless consumer experience all in real time.
We are looking for a risk modeling/data scientist to join the Risk team to build out models in real-time decisioning, portfolio construct/transitions, and customer behavioral dynamics and propensity. You will have a chance to work on real problems in all aspects of modeling from exploring new data sources, feature engineering, adopting new model specifications, implementations to managing model performance and quality, have a steep learning curve, make tangible contributions both you and the organization will be able to see, and be an integral part of the team.
Things you will do:
- Build models and predictive tools that answer actual questions to make Bread be and do better in a measurable fashion
- Critically interrogate data and synthetize learnings and insights
- Investigate new data sources, design model specifications and optimize model performance
- Maintain model inventory, performance thresholds, and real-time model performance monitoring
- 1+ years of experience in building high-performing models. Preference given to credit/fraud risk modeling experience
- Hands-on experience and familiarity with machine-learning techniques, statistics, and optimization
- Ability to work with cross-functional teams, implement models, thought leadership to drive data science innovation
- Ability to think and interrogate data critically
- Have the drive and desire to learn, question and experiment in an evidence-based way
- Native in R, Python or similar and SQL is a necessary
If this is you, submit a cover letter and resume to apply!