Note: The job is a remote job and is open to candidates in USA. Kreate is a family-owned plastic injection molding company that creates consumer goods and operates across multiple states. The Senior Data Scientist owns analytical methods and models supporting demand, inventory, production capacity, scheduling, experimentation, and business metrics. The role also leads and mentors a Data Scientist and partners with engineering, finance, corporate development, and business leadership to develop production-ready analytical tools and models.
Responsibilities
- Own the production planning model, including demand forecasting, safety stock and inventory targets, and forward production plans across plants
- Build capacity and scheduling optimization models, including press and mold assignment, site balancing, and utilization targets while accounting for real-world constraints such as tool availability
- Own metric governance and establish consistent definitions for key business metrics, including labor as a percentage of production sales value, OEE, and net sales
- Reconcile metric definitions and calculations across the lake house, Power BI, and business applications to establish a consistent source of truth
- Design, execute, and analyze experiments with retail partners, including price and assortment tests
- Partner with engineering to build LLM-assisted analytics tools, such as natural-language question-and-answer capabilities over the data warehouse, with appropriate evaluation methods, accuracy standards, and guardrails
- Support finance and corporate development with analytical modeling for acquisitions, capital projects, facility decisions, and other strategic initiatives
- Lead and mentor the Data Scientist, providing guidance on analytical approaches, technical development, and communication
- Establish and maintain review standards for analytical code, methodologies, documentation, and business communication
- Present analytical findings, models, and recommendations to executive leadership and clearly explain and defend the underlying methodology and assumptions
- Collaborate across data, engineering, operations, finance, and commercial teams to translate complex business problems into practical analytical solutions
Skills
- 5+ years of experience in data science, operations research, advanced analytics, or a related field, ideally within manufacturing, supply chain, consumer packaged goods (CPG), or a similar environment
- Demonstrated experience applying forecasting and inventory methods in production environments, including intermittent and hierarchical demand forecasting and service-level-based safety stock
- Experience with optimization techniques such as linear programming (LP) or mixed-integer programming (MIP), using tools such as OR-Tools, PuLP, Pyomo, or similar platforms, or demonstrated experience developing practical scheduling heuristics
- Expert-level SQL and Python skills, with experience developing production-quality code maintained in Git
- Demonstrated ability to investigate and reconcile conflicting metrics or reports and establish a consistent definition or source of truth across teams
- Strong analytical judgment and the ability to evaluate assumptions, methodologies, and limitations
- Excellent communication skills, including the ability to present complex analytical concepts to executive leadership and confidently explain and defend analytical methods under questioning
- Demonstrated leadership or mentoring experience, with the ability to establish standards and develop less-experienced data science professionals
- Experience with injection molding, plastics manufacturing, or multi-plant Sales and Operations Planning (S&OP)
- Experience with Microsoft Fabric and Power BI semantic models
- Experience using LLM APIs, including Anthropic or Open AI, in production analytics tools or applications
- Experience formally managing or mentoring analysts or data scientists
Benefits
- Remote work arrangement
Company Overview