Senior Data Scientist (Credit Risk)
Quick Summary
At Braviant, we believe in hiring great talent and offering them the flexibility to achieve great results unbounded by geography. Braviant is offering a fully remote option for anyone in the U.S. who wants to join our team and help us grow.
We are building and scaling a high-performance consumer lending platform and are looking for a Senior Data Scientist to drive credit decisioning across the loan lifecycle.
This role sits at the intersection of credit strategy, fraud, and analytics, directly impacting approval strategy, loss performance, and portfolio profitability.
You will build and deploy models that inform key decisions around who we approve, how we price risk, and how we manage portfolio performance.
This is a hands-on, high-impact role suited for someone who is business-oriented, data-driven, and biased toward action, not just model development.
You will partner closely with Credit, Fraud, Servicing, Product, and Engineering to translate data into clear, actionable decisions that improve approval quality, reduce early loss, and drive sustainable growth.
This role is Addison, TX-based with a 4-day in-office requirement and 1-day work from home.
- Develop and deploy predictive models across the credit lifecycle (acquisition, risk, and collections) with a focus on improving approval quality and loss performance.
- Translate model outputs and analysis into actionable credit strategy, including approval cutoffs, segmentation, and decision rules.
- Analyze portfolio performance (FPD, delinquency, loss) to identify key drivers of deterioration and recommend targeted actions.
- Evaluate tradeoffs between approval rate, loss, and profitability, and recommend strategies to optimize portfolio performance.
- Distinguish fraud risk vs credit risk, improving early default performance and reducing losses.
- Design and execute experiments (A/B tests, champion/challenger frameworks) to evaluate strategies and drive continuous improvement.
- Work with Product and Engineering to implement decisioning logic into production systems and ensure accurate execution.
- Monitor model and strategy performance over time, identifying drift, instability, or unintended impacts on portfolio outcomes.
- Collaborate cross-functionally with other departments to ensure decisions align with business goals and risk appetite.
- Degree in Data Science, Applied Mathematics, Statistics, Economics, Computer Science or a related field
- 5-7 years of professional experience in Data Science, Analytics or a related field within FinTech or online lending space.
- Advanced proficiency in Python for programming, data analysis, and predictive modeling
- Proficiency in SQL, Excel and experience with data visualization tools
- Excellent knowledge in applied statistical methods and experience using various predictive machine learning techniques including: linear models, decision trees, boosting, and ensemble models
- Knowledge of optimization, stochastic processes, experimental design, A/B testing and bootstrapping
- Passion for keeping your skills up to date and exploring new methodologies
- The ability to distill complex problems and analysis into a clear and concise narrative
Nice to Have
~1 min read- Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment.
- Hands-on experience applying AI to credit risk management
Compensation at Braviant is competitive and commensurate with experience. Details will be discussed with qualified candidates during the interview process. In addition, we provide:
- Comprehensive healthcare including medical, dental, and vision coverage
- Generous paid time off, including PTO, sick time, and 13 company holidays
- 401(k) with company contribution
- Participation in annual discretionary bonus plan
- Regular team and company gatherings
Location & Eligibility
Listing Details
- Posted
- May 11, 2026
- First seen
- May 11, 2026
- Last seen
- May 13, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- May 11, 2026
Signal breakdown
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