SI&OP Data Scientist

Slate Auto•Troy, MI

6d•$131,773 - $233,781

About The Position

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.

Requirements

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 SmartSheets, Tableau, Alteryx, or other scripting tools.
Strong verbal and written communication skills, with an understanding of how to present complex data in easily understood ways to multiple levels with the business.
Strong problem solving capabilities, with an attention to detail.
Comfortable in start-up environments. You can roll up your sleeves to do the work and build, or recommend the tools needed to be successful as the company grows.
A proactive, “one company” teammate with a continuous improvement approach, equally comfortable with warehousing practices, material management, business planning, and financial implications.
Capability to work cross-functionally with external partners and internal teams, building strong relationships that produce positive results.
Applicants must be authorized to work in the United States on a permanent basis. We are unable to offer visa sponsorship at this time.

Responsibilities

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.