About the role
Why TrueML? TrueML is a mission-driven financial software company that aims to create better customer experiences for distressed borrowers. Consumers today want personal, digital-first experiences that align with their lifestyles, especially when it comes to managing finances. TrueML’s approach uses machine learning to engage each customer digitally and adjust strategies in real time in response to their interactions. The TrueML team includes inspired data scientists, financial services industry experts and customer experience fanatics building technology to serve people in a way that recognizes their unique needs and preferences as human beings and endeavoring toward ensuring nobody gets locked out of the financial system. As a Sr. Data Scientist, you aren’t just building models; you’re an architect of decision-making. You possess a battle-tested understanding of both patterns and anti-patterns, navigating the "why" behind the data to drive our automated debt collection strategy forward. We’re looking for someone with an extreme ownership mindset who can identify tech debt, predict where code might break before it does, and mentor the next generation of data experts. You’ll be the go-to expert for critical portions of our codebase, translating complex business
requirements into high-impact technical reality. \n Work-Life
Benefits Unlimited PTO Medical benefit contributions in congruence with local laws and type of employment agreement
What You'll Do: Drive the Roadmap: Contribute innovative ideas to the technical and product roadmaps, estimating effort for discovery and high-velocity execution. Collaborate & Translate: Work closely with product managers and engineers to turn abstract business needs into scalable technical implementations. Predict & Prevent: Proactively solve code challenges by anticipating breaks and considering the downstream impacts of your solutions. Own the Lifecycle: Take full end-to-end responsibility for complex initiatives, from initial scoping with stakeholders to production deployment and maintenance. Lead by Example: Improve departmental code quality through thoughtful, detailed code reviews and by establishing team-level best practices for AI-assisted development. Innovate: Stay ahead of industry trends, introducing new techniques and keeping a rigorous record of tech debt with clear paths to resolution. Solve Complex Problems: Handle the most challenging issues in your area of expertise independently, serving as the technical authority for
