What you'll do
Operational data warehouse and infrastructure
- Design and build the operational data warehouse: integrating data from ERP (NetSuite), CRM (Salesforce), and other business systems into a unified, reliable analytics layer.
- Build and own ETL pipelines, data quality, and governance in close partnership with Business Systems on architecture and system integrations.
Demand forecasting and S&OP
- Build and own statistical and ML-driven demand forecasting models that feed the monthly S&OP cycle and inform capacity, procurement, and production planning.
- Partner with Sales, Finance, and Operations leadership to align forecast inputs and provide real-time visibility into demand signals and supply constraints.
- Build the Operations reporting suite: automated dashboards and KPI tracking for executive visibility.
Central planning and supply chain analytics
- Design and maintain analytical models for inventory optimization, lead time analysis, supplier performance tracking, and capacity utilization.
- Build predictive models to anticipate supply disruptions, demand variability, and cost escalation.
Costed BOMs and margin analytics
- Own the data pipeline and reporting layer for costed bills of materials (BOMs) ensuring visibility into material costs, labor, and overhead across product lines.
- Develop scenario models to evaluate the cost impact of design changes, sourcing decisions, and volume shifts.
Minimum Qualifications
- 5+ years in data science, analytics engineering, or operations/revenue analytics.
- Proficiency in Python and SQL; experience with cloud data platforms (Snowflake or equivalent).
- Hands-on experience building forecasting models and data pipelines in a production environment.
- Ability to translate complex model outputs into clear narratives for non-technical stakeholders and senior leadership.
- Experience working cross-functionally with Finance, Sales, Supply Chain, or Operations.
- Bachelor’s degree in supply chain, engineering, business, or related field.
Preferred Qualifications
- Experience with supply chain analytics, S&OP, costed BOMs, or manufacturing/operations environments.
- Familiarity with ERP or WMS data models (NetSuite, SAP, or similar).
- Generative AI or LLM integration experience applied to operational or analytical workflows.