Sr. Data Scientist I
WFA Digital Insight
TrueML isn’t just another fintech; it’s a mission‑focused outfit that uses machine learning to keep borrowers from being locked out of the financial system. The Senior Data Scientist seat sits at the intersection of product, engineering and finance, giving the right candidate real influence over how automated debt‑collection logic is built and refined. What sets this role apart is the expectation to own critical code pathways, anticipate technical debt, and mentor junior talent—all while translating business nuance into scalable models. Candidates will work alongside a tight‑knit group of data engineers and product experts, reporting into a product‑centric leadership team that values extreme ownership and proactive problem solving.
Job Description
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. Work-Life
Benefits
Unlimited PTO Medical benefit contributions in congruence with local laws and type of employment agreementWhat 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 the team.Who you are
: The Seasoned Pro: You have 5+ years of relevant experience and a strong foundation in statistics, machine learning, or a similar quantitative field. The Mentor: You find fulfillment in pairing with other engineers to share knowledge and support team members in preventing burnout. The Communicator: You can facilitate high-stakes meetings with both technical and non-technical stakeholders, leaving everyone with a clear sense of the "so what." The Strategist: You understand the business impact of your projects and can effectively communicate the technical roadmap to leadership. The Finisher: You have the grit to see complex epics through to completion, valuing even the "undesirable" work if it helps the team move faster.What you Bring
: Cloud & ML Infrastructure: Proven experience leveraging AWS (S3, Lambda) and SageMaker to build, train, and deploy machine learning models at scale. Technical Proficiency: Mastery of Python and deep experience with ML techniques like regression, classification, and optimization. Architectural Wisdom: The ability to make well-reasoned design trade-offs and provide high-level advice across multiple components of a domain. AI-Forward Mindset: Experience using AI tools to rapidly prototype features and the ability to define validation standards for AI-generated code. Experimentation Expertise: A solid understanding of product experiment design, analytics, and statistically rigorous analysis. Tooling Fluency: Familiarity with modern ML frameworks (e.g., TensorFlow, PyTorch) and libraries like Pandas/Numpy. Operational Excellence: Experience building model development pipelines and productionizing models at scale. We are a dynamic group of people who are subject matter experts with a passion for change. Our teams are crafting solutions to big problems every day. If you’re looking for an opportunity to do impactful work, join TrueML and make a difference. Our Dedication to Diversity & Inclusion TrueML is an equal-opportunity employer. We promote, value, and thrive with a diverse & inclusive team. Different perspectives contribute to better solutions, and this makes us stronger every day. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.How to Stand Out
- Highlight any production‑grade AWS deployments (S3, Lambda, SageMaker) in your résumé; concrete examples win interviews.
- Prepare a short case study showing how you identified and fixed tech debt in a past project.
- Bring a portfolio of end‑to‑end ML pipelines, emphasizing data preprocessing, model validation, and monitoring.
- Practice explaining a complex model to a non‑technical audience; interviewers will test your communication skills.
- Research TrueML’s mission and be ready to discuss how your work can improve borrower experiences.
- During salary discussions, mention the value of unlimited PTO and remote‑work flexibility as part of total compensation.
- Watch for vague promises about “remote stipend” without specifics; ask for clarity on equipment support before accepting.
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