Lead Data Scientist, Demand Forecasting

Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and trucks and will do so once again. But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work. The Scout brand is all about respect. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. Respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute. And respect for our customers by developing two powertrains that meet their requirements — an all-electric powertrain as well as the Harvester™ range extender powertrain which includes a built-in gas-powered generator with an estimated 500 miles of combined range. At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion. Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now! Role Overview Scout Motors is building its first enterprise demand forecast - and there's no sales history to build it on.   As a VW Group–backed EV company in the run-up to launch, Scout has reservations data, an enthusiastic and loyal community, and a product about to enter the market — but not the years of historical sales a demand model usually leans on. That's the problem this role owns: building a rigorous, probabilistic forecast from the signals that do exist, and growing it into the analytical engine of Scout's planning system as real demand data arrives.   This is the first dedicated modeling seat in Integrated Business Planning. You'll develop the demand forecasting model and own the data behind it — then partner with IT and Product Management to productionize it into the digital IBP product Scout is building, so the forecast lives where the business actually plans and decides. What you’ll do Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following: Build Scout's first demand forecasting model — probabilistic rather than point-estimate, forecasting unconstrained demand at the grain the business plans on. Convert reservation backlog with explicit probabilities, phase the timing of that conversion, and layer in organic demand as its own signal.    Solve the cold-start problem — stand up a credible forecast before there's sales history, using reservations, configurator and order data, market analogs, and structured priors — then systematically replace assumptions with data as the market gives it to us.    Own the demand data end to end — source, define, and steward the data that feeds the forecast; build the pipelines and the feature/data layer; own data quality and the shared definitions everyone downstream depends on.    Partner across the business to get the inputs and outputs right — work with the teams that own the signals feeding the forecast and the teams that consume it, so the model is grounded in real inputs and lands in a format the business can actually use.   Make the forecast legible — document methodology and assumptions, quantify uncertainty honestly, and explain the model's logic clearly to non-technical stakeholders in Finance, Commercial, Production, and Procurement.    Productionize with IT and Product — partner with engineering to move the model from notebooks into the IBP digital product (pipelines, deployment, monitoring, retraining)   Stand up forecast measurement — back-testing, accuracy tracking, and model monitoring, so the forecast improves on a known cadence as post-launch data accumulates and the model is retrained against reality.    Lay the foundation for what's next — build the data and modeling base that Scout's future AI/ML planning capabilities will extend.   Location & Travel Expectations : This role may be based out of the  Scout Motors corporate headquarters in Charlotte, NC .  This role requires 4-5 days per week in the office, with regular in-person meetings and events.  Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time. What you’ll bring  We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring:  12+ years of applied data science or forecasting, or equivalent experience — you've built and shipped statistical or ML models that other people depend on, not just one-off analyses.    MS of PhD in a quantitative discipline (statistics, applied math, physics, operations research, economics, or similar), or equivalent applied experience   A strong probabilistic and time-series modeling foundation — hierarchical, Bayesian, or other methods suited to granular, sparse, and uncertain demand. You reason in distributions, not just predictions.    Fluent in Python and the modern modeling stack, strong SQL , and comfortable owning data end to end — pipelines, quality, and definitions, not just the model that sits on top.    Experience forecasting with sparse, new-product, or cold-start data — analogs, priors,