Senior Data Scientist (Credit Risk)

Senior Data Scientist (Credit Risk) Braviant Holdings - 4.0 Dallas, TX Job Details Full-time 13 hours ago Benefits Health insurance Dental insurance 401(k) Paid time off Work from home Vision insurance 401(k) matching Qualifications Data visualization software proficiency SQL Statistical modeling Experimental design Predictive analytics A/B testing Lending Data science Implementing machine learning algorithms Python Excel data analysis Database software proficiency Full Job Description 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 also have an office space in the heart of downtown Chicago for those who prefer to get out of the house and collaborate with some colleagues in person.

Who we are:

Braviant is a leading provider of tech-enabled credit products that combines breakthrough technology and cutting-edge machine learning to transform how people access credit online. Our next-generation approach to lending reduces credit barriers and creates a Path to Prime to help millions of underbanked consumers build credit history, reduce their cost of borrowing, and take control of their personal finances. Braviant has been named multiple times to the Inc. 5000 list of fastest growing private companies and has been recognized as a Best Place to Work by Crain's Chicago, BuiltIn Chicago and American Banker. 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. What You'll Be Doing 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. What You Will Bring Required 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 Preferred Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment. Hands-on experience applying AI to credit risk management Benefits &Perks 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 What it's like to work here: We're about achieving results while having fun along the way. We believe in solving problems together and building on each other's ideas. Our teams are comprised of smart, curious individuals and we encourage everyone to think like an owner, take initiative and drive their careers. Our broad roles provide tremendous opportunities for individuals to acquire new skills, gain exposure to all areas of the business, and quickly see their impact at Braviant. Want to learn more? Check us out on Glassdoor, BuiltIn and our Newsroom We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.