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Braviant Holdings

Data Scientist, Lead

Sorry, this job was removed at 02:09 p.m. (CST) on Tuesday, Feb 17, 2026
Remote
Hiring Remotely in USA
130K-160K Annually
Remote
Hiring Remotely in USA
130K-160K Annually

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Please note: 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 credit products which combine breakthrough technology and cutting-edge machine learning to transform how people access credit online. The Company’s 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.

Position Summary:
We are looking for an experienced Data Scientist to develop, implement and optimize the core machine learning models that drive our business. The right person for this role has strong technical skills with a solid background in machine learning and analytics. You will play a central role in delivering scalable, interpretable, and compliant models that drives Braviant’s business
performance while collaborating closely with partners across Marketing, Credit, Technology, and Compliance. This person is biased towards action and proactively seeking new solutions.

What you’ll be doing:

  • Develop, implement and monitor performance of machine learning models across loan life cycle
  • Design and implement A/B testing frameworks to validate hypothesis, analyze outcomes and drive continuous improvement
  • Proactively perform data exploration and analysis to identify new opportunities to enhance model performance and business impact
  • Collaborate with cross functional stakeholders to define and monitor business KPIs and influence product strategy
  • Partner with Technology teams to build out data science pipelines to support continuous testing, optimization and implementation of new models
  • Ensure rigorous documentation, governance, and model validation in accordance with financial services regulatory requirements

What you’ll bring:

  • Degree in Data Science, Applied Mathematics, Statistics, Economics, Computer Science or a related field
  • 4-6 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

Benefits and Perks
• Medical benefits paid by employer/employee split of 80/20
• Participation in discretionary bonus plan
• Dental and Vision covered at zero cost to you for employee only coverage
• PTO, Sick and Floating Holidays
• 14 Company Holidays
• Participation in the Company Profits Interest Units long term incentive plan
• Remote work environment
• Monthly Internet stipend
• Team and company events/get togethers

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

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