At January, we work to ensure that borrowers who fall behind on debt are treated with dignity. Owing to outdated processes and bad actors, traditional debt collection is rife with harassment and fraud. Our products tackle this by helping financial institutions modernize collections, giving borrowers simpler and more compassionate ways to get back on track.
As a data scientist, you'll play a significant role in shaping product direction through the development of machine learning models and experimentation processes. Working closely with product managers, analysts and engineers, you'll identify and execute on opportunities to transform structured business logic into ML-driven decision engines that directly affect how borrowers get out of debt and back to financial stability. You'll help ensure that each individual borrower is treated fairly, while still receiving customized payment options that suit their unique financial circumstances.
Your impact: You'll play a key role in shaping the borrower experience, making debt collection simpler and more empathetic while improving recoveries. This might involve designing reinforcement learning models to automate decision-making, contributing to the development of LLM-based tools that provide borrowers with 24/7 support, and running experiments to optimize our communications strategy. Your work will ensure that borrowers receive the right outreach at the right time, enhancing engagement and repayment outcomes.
On the client side, you'll help creditors build a deeper understanding of borrower behavior, enabling them to make well informed decisions. You'll develop ML-based recommendations that guide creditors in having more effective interactions with their borrowers, while also building visualizations that make complex insights easy to understand and act on. Your contributions will strengthen January's position as a trusted data partner to creditors.
You'll also have a hand in shaping January's data infrastructure, influencing how we gather, unify, and leverage proprietary data to create a comprehensive view of consumer financial behavior. Your work will help unlock insights that no one else can replicate, giving us a competitive edge.
Beyond direct contributions, you'll elevate the analytics team by sharing your expertise in statistics, data science practices, and the broader problem domain. Through code reviews, pair programming, documentation, and mentorship, you'll help your peers grow and ensure the team operates at the highest level of sophistication. Your impact will extend beyond your own projects, strengthening January's overall data capabilities.
You may be a fit if you have: - 4+ years of experience in relevant analytics roles with at least 2 years of experience in data science, ideally at a venture-backed, high-growth startup
- Advanced statistical knowledge, ability to go well beyond the basics of bias, independence, significance testing, confidence intervals, and correlations
- Mid-level to advanced knowledge of R or Python, with preferred experience building and applying statistical models in either of these languages
- Experience managing experiments
- Mid-level to advanced SQL proficiency and ability to write simple, maintainable queries
- A track record of driving complex decisions involving stakeholders both inside and outside your team