Product Data Scientist

Learn the business, find the problems worth solving, and build the data products and models that solve them, working AI-first from the data layer all the way to the app.

SelectFI builds AI-powered tools for the automotive finance space, helping dealerships and lenders make smarter, faster credit decisions through predictive modeling and intelligent workflows.

The lenders have always had the data. SelectFI gives that same advantage to dealers — predicting which lender will approve a deal, and how it should be structured, before submission. That moves F&I teams from guesswork to precision: deals are penciled right the first time, approvals come faster, credit-pull costs go down, and lenders see cleaner submissions.

This role is part product thinker, part builder. You’ll learn how dealers, lenders, and our own sales and customer success teams work, find the problems worth solving, and build the data, models, and app features to solve them, often in days with AI. You won’t be handed a queue of tickets: you’ll write them, prioritize them, and measure your work by its results. Along the way, you’ll own SelectFI’s lender approval models end to end.

• Spend real time with sales, customer success, and our dealerships to learn how they work and where they get stuck.

• Find new data worth collecting and new uses for the data we already have, such as new product lines, reports dealers will get value from, or tools that help our sales team close deals.

• Turn what you learn into your own tickets: define the problem, size the payoff, set priorities, and keep your plan visible to the team.

• Prototype fast, often with AI tools, put the result in front of real users, and measure whether it worked.

• Build, retrain, and monitor the ML models that predict which lenders will approve a deal and at what rate, as well as building new models to support new product lines.

• Report regularly on prediction performance: where the models miss, and why.

• Analyze dealer feedback on predictions (thumbs up or down, with a reason) and turn it into model and product fixes.

• Take new lenders live on a dealership’s go-live date, turning lender guidelines and rate sheets into rate tables and rules.

• Find a sound prediction strategy for a new lender, even when there is little or no historical decision data.

• Maintain lender eligibility rules, rate tables, and credit logic (LTV, DTI, score bands) in our rules engine as lenders change their programs.

• Stand up ETL from dealer systems, CRMs, credit bureaus, and data providers into our Redshift warehouse, and own data quality from source to model.

• Use AI tools to pull data out of PDFs and messy exports, scaffold pipelines, and write and test SQL in hours rather than days.

• Take features all the way to the user. When a model or data change needs a new field, screen, or report in the app, you build the first working version yourself with AI coding tools, and the app team reviews it rather than building it from scratch.

• Adapt our models to new verticals such as RV lending, where credit scores, deal structures, and rate tables differ from auto.

• Answer business questions with data, such as profitability analyses, which loan terms dealers actually fund, and dashboards for the team and customers.

• Work with sales, customer success, and dealership staff to chase down data, understand lender behavior, and trace a bad prediction back to its cause.

• 4+ years building and deploying predictive models in production, ideally classification models on tabular data. Startup experience preferred.

• Strong Python for data work and modeling, including the standard ML libraries for tabular data.

• Advanced SQL and hands-on experience in a cloud data warehouse (we use Redshift on AWS).

• Experience building and maintaining ETL pipelines, not only working from clean tables, and shipping code through Git and pull requests.

• An AI-first way of working, with range beyond data and ML: you use AI tools every day to reshape data, stand up pipelines, and get working features into unfamiliar code, front end or back end, instead of waiting for someone else to pick them up. And you check what they produce.

• Comfort working directly with sales, customer success, and dealership staff, and explaining data clearly to people who aren’t technical.

• You define the work instead of waiting for it: you learn the business, decide what matters, write your own tickets, and unblock yourself. A startup, a solo data role, or a project you built from zero all count.

• Inventive and curious, with a product mindset: you look at a dataset and see a feature, a report, or a new product, and you judge your work by its results for dealers and the business.

• Bachelor’s degree in a quantitative field, or equivalent practical experience.

• Experience in consumer lending, credit risk, or auto or RV finance.

• Experience in product management, solutions engineering, or another customer-facing role.

• Some hands-on web or app development experience, front end or back end.

• Familiarity with dealership systems such as RouteOne, Dealertrack, or dealer CRMs.

• Experience with model monitoring, feedback loops, or fair-lending review for credit models.

30 days: You know our prediction pipeline, data warehouse, and lender rules engine, you’ve shipped a few pull requests, and you’ve met engineering, customer success, and a few of our dealerships.

60 days: You’ve shipped a significant model improvement or feature, extended a data pipeline with AI tools, and help lead regular reviews of model performance and feature priorities.

90 days: You set your own priorities against company goals, have taken at least one idea of your own from a conversation with sales or customer success to a shipped result, and have a written point of view on what we should build in the next few months.

$130,000–$170,000 base salary, plus equity, based on experience. Benefits include health and dental insurance, unlimited PTO, and flexible remote, hybrid, or in-office work.

Ownership: You’ll own SelectFI’s approval models, lender data, and pipelines end to end, and help decide what we build with them.

Growth: As SelectFI scales, this role can grow into leading our data science function and its first hires.

Environment: Small team, fast feedback, direct access to leadership. Based in Buffalo, with flexible remote, hybrid, or in-office options.

Apply with your résumé and a short note on something you've built that you're proud of — a problem you spotted and solved with data, a tool you built quickly with AI, or a model running in production. We read every application.

SelectFI is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by applicable law. We provide reasonable accommodations for qualified individuals with disabilities — to request one, contact [email protected]. Applicants must be authorized to work in the United States; we do not currently offer visa sponsorship.