Who We Are:

Braviant is a Chicago-based fintech startup that combines breakthrough technology and machine learning to empower underbanked consumers with better credit solutions. Our team of technologists, data scientists and fintech veterans develops proprietary decision algorithms that look beyond a traditional credit score to more accurately assess a person’s true ability and willingness to repay. This next-generation approach to lending is reducing credit barriers and creating a Path to Prime to help the 43% of U.S. adults with non-prime credit reduce their cost of borrowing, build credit history, and achieve better financial outcomes.

The Role:

We are looking for a talented Sr. Data Engineer to implement, monitor and maintain a number of statistical models and underwriting processes. The right person for this role will have a strong background in data platforms and development, and experience working in the consumer lending industry.

Job Responsibilities:

• Collaborate with Analytics and Technology teams to implement machine learning models, in R and Python, on our underwriting platform.
• Support continuous testing, optimization, and streamlined implementation of new models and strategies. Produce concise, maintainable code and scripts to support these processes.
• Create business reporting and monitoring on Analytics models, using SQL, across multiple data and customer sources. Troubleshoot and escalate potential issues as they arise.
• Create and implement test plans to ensure proper functionality and code quality. Prevent bugs and code regression as new models are released.
• Work with Technology team to implement software development best practices, adhere to Braviant's SDLC and follow established release process.
• Optimize data flows for existing Analytics processes, such as direct mail marketing and bank statement integration. Speed them up where possible, and make them fault tolerant.

Requirements:

• BA or MA in Computer Science, Data Science, Applied Mathematics, Statistics, Economics or other quantitative field is preferred.
• 3+ years of experience in a similar role, with a preference for unsecured consumer lending experience.
• Expert proficiency in languages used for data manipulation and statistical analysis, including R, Python, and SQL.
• Strong familiarity with git and GitHub/Bitbucket. Ability to understand and follow an agile SDLC, working with multiple teams to test and plan a release.
• Basic familiarity with a variety of predictive modeling techniques including logistic regression, boosting, and decision trees. Ability to implement and validate models derived from these techniques.
• Proficiency with Unix scripting, Java, AWS (EC2 and S3), and/or Jenkins is preferred.
• Ability to collaborate with cross-functional teams to solve complex problems and develop pragmatic solutions under tight deadlines.
• Motivated by working in a high-growth, fast-paced and iterative environment.

Looking for perks?• 3% 401K employer contribution that is immediately vested• Health benefits? We’ve got you fully covered.• Flexible work schedule with results-based culture• Generous PTO• Annual professional development allowance • Fully stocked kitchen• Casual dress code• Team building events and happy hours• Significant career upside as our business grows