Job description

Title: Senior Data Scientist Function: Credit Risk Reports to: Head of Credit Level: Mid-Level / Senior Location: Addison, TX (5 days/week in-office) Please note: This position is open to candidates within commuting distance to the DFW metro area only. Applicants must reside in Texas and be authorized to work in the United States. Applications from candidates outside of Texas will not be considered at this time. While we appreciate interest from all applicants, Braviant Holdings is unable to sponsor visas at this time. Who We Are Founded in 2015 and based in Chicago, IL, privately held Braviant Holdings, LLC is a leading provider of tech-enabled consumer credit products that combine 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®, helping 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. We are a lean team of approximately 40 people. Everyone rolls up their sleeves here, including this role. About the Role 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. 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 Braviant is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, marital status, veteran status, disability status, or any other characteristic protected by applicable law.

Requirements

Must-haves

Title: Senior Data Scientist
Function: Credit Risk
Reports to: Head of Credit
Level: Mid-Level / Senior
Location: Addison, TX (5 days/week in-office)
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
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

Nice-to-haves

Experience in subprime consumer lending, fintech, payments, or another regulated financial services technology environment.
Hands-on experience applying AI to credit risk management

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonsqlai

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off