Lead Data Scientist, Demand Forecasting

Scout Motors • Charlotte, NC

2h • $160,000 - $192,500 • Onsite

About The Position

Scout Motors is building its first enterprise demand forecast, a critical role for the company as it approaches launch. As a VW Group–backed EV company, Scout has reservation data, an enthusiastic community, and a product about to enter the market, but lacks historical sales data. This role is responsible for building a rigorous, probabilistic forecast from existing signals and evolving it into the analytical engine of Scout's planning system as real demand data becomes available. This is the first dedicated modeling position within Integrated Business Planning. The successful candidate will develop the demand forecasting model, own the data associated with it, and collaborate with IT and Product Management to productionize it within Scout's digital IBP product, ensuring the forecast is integrated into the business's planning and decision-making processes.

Requirements

• 12+ years of applied data science or forecasting experience, with a proven track record of building and deploying statistical or ML models that are depended upon by others.
• MS or PhD in a quantitative discipline (statistics, applied math, physics, operations research, economics, or similar), or equivalent applied experience.
• Strong probabilistic and time-series modeling foundation, including hierarchical, Bayesian, or other methods suitable for granular, sparse, and uncertain demand. Ability to reason in distributions.
• Fluent in Python and the modern modeling stack, strong SQL skills, and experience owning data end-to-end (pipelines, quality, definitions).
• Experience forecasting with sparse, new-product, or cold-start data, using methods like analogs, priors, and judgment-augmented approaches, with an understanding of their limitations.
• Experience putting models into production with engineering and product teams, considering deployment, monitoring, and retraining.
• Proficiency in using AI coding tools (e.g., Claude Code, Copilot, Cursor) for building, prototyping, and shipping code faster, with the judgment to apply them effectively.
• Ability to translate technical work for non-technical audiences and defend forecasts to senior, cross-functional stakeholders.
• High-ownership mindset, comfortable in a fast-moving, build-it-yourself environment with maturing data and priorities.

Nice To Haves

• Experience in automotive, manufacturing, or other physical-product demand forecasting.
• Experience with demand sensing or hierarchical forecasting.
• Experience with ML Ops.
• Experience embedding models inside a digital product.

Responsibilities

• Build Scout's first demand forecasting model, focusing on probabilistic forecasting of unconstrained demand at the business planning grain. This includes converting reservation backlog with explicit probabilities, phasing conversion timing, and incorporating organic demand as a distinct signal.
• Solve the cold-start problem by establishing a credible forecast before sales history exists, utilizing reservations, configurator and order data, market analogs, and structured priors, with a plan to systematically replace assumptions with data as it becomes available.
• Own the demand data end-to-end, including sourcing, defining, and stewarding data for the forecast; building data pipelines and the feature/data layer; and ensuring data quality and shared definitions for downstream users.
• Partner across the business to ensure accurate inputs and outputs for the forecast model, collaborating with teams that own input signals and those that consume forecast outputs to ensure the model is grounded and usable.
• Make the forecast legible by documenting methodology and assumptions, honestly quantifying uncertainty, and clearly explaining the model's logic to non-technical stakeholders in Finance, Commercial, Production, and Procurement.
• Partner with engineering to productionize the model, moving it from notebooks into the IBP digital product, including pipelines, deployment, monitoring, and retraining.
• Establish forecast measurement processes, including back-testing, accuracy tracking, and model monitoring, to ensure continuous improvement as post-launch data accumulates and the model is retrained.
• Build the data and modeling foundation for Scout's future AI/ML planning capabilities.

Benefits

• Competitive compensation
• Medical, dental, vision and income protection plans
• 401(k) program with employer match and immediate vesting
• 20 days planned PTO, as accrued
• 40 hours of unplanned PTO
• 14 company or floating holidays, annually
• Up to 16 weeks of paid parental leave for biological and adoptive parents of all genders
• Paid leave for bereavement, jury duty, voting time, or military leave

What This Job Offers

• Job Type: Full-time
• Career Level: Senior