SI&OP Data Scientist

At Slate, we’re building safe, reliable vehicles that people can afford, personalise and love—and doing it here in the USA as part of our commitment to reindustrialization. The spirit of DIY and customization runs throughout every element of a Slate, because people should have control over how their trucks look, feel, and represent them.

Slate is looking for an energetic, organized, experienced SI&OP Data Scientist to join our growing team. As an SI&OP Data Scientist, you will own the forecast models used for supporting the Sales, Inventory, and Operations Planning process. You will do this through building and deploying statistical, AI, and Machine Learning models to forecast demand (sales planning), optimize inventory levels, and align procurement and production activities to meet customer requirements and business objectives.

You will own the analytical side of SI&OP across the business units of Slate, including vehicle (consumer and fleet), service parts, accessories, and apparel and merchandise. You will work cross-functionally with the individual business units, Sales, Marketing, Brand, Engineering, Purchasing, Production, and Finance to develop a rolling 12
-24 month executable business plan.

Own the predictive time-series, AI, and Machine Learning models used for forecasting product sales across Slate’s business units while driving the forecast down to various geographies and segments. Monitor forecasts accuracy, forecast bias, and other measures to drive ongoing forecast model refinement to improve forecast quality. Partner with SI&OP Analysts to run root-cause variance analyses and evaluate planning deviations. Translate complex outputs into clear, actionable operational insights for non-technical stakeholders.

Design models to drive inventory optimization, safety stock development, and supply capacity constraint reduction plans. Build and maintain forecasts and processes that allow scenario planning based on different demand and supply inputs. Translate complex business questions into structured scenario analysis to evaluate trade-offs between service levels, costs, and operational risks. Own and scale data pipelines and data quality driving to automated reporting dashboards in order to track model performance, forecast accuracy, inventory optimization and other KPIs.

Develop, track, and report key performance indicators (KPIs) related to SI&OP, including, forecast accuracy (at multiple time lags), inventory turns, service levels, and production / procurement performance. Support the monthly SI&OP cycle through meeting presentation preparation, analysis to support SI&OP recommendations, and SI&OP KPI report outs. Drive a continuous improvement mindset within SI&OP, focusing on SI&OP processes, forecast accuracy, inventory management, and overall process efficiencies.

• Bachelor’s Degree in Data Science, Mathematics, or Statistics (with an emphasis on Business Administration) or Business Administration, Supply Chain Management, Finance (with an emphasis on Data Analytics) or equivalent is required.
• 6+ years of experience in Data Science, with hands‑on experience working within SI&OP, Demand Planning, or Business Management / Strategy strongly preferred.
• Experience with AI, machine learning, and predictive analytics to create forecasting models.
• Strong analytical skills, with sufficient understanding of data interpretation and forecasting models (both statistical and non-statistical).
• Proficiency in Microsoft Excel and/or other data analysis tools, such as Smart Sheets, Tableau, Alteryx, or other scripting tools.
• Strong verbal and written communication skills, with an understanding of how to present…