Senior Data Scientist

The Senior Data Scientist owns the analytical methods and models that support critical business decisions across demand, inventory, production capacity, scheduling, and core business metrics. The role combines advanced analytics, forecasting, optimization, experimentation, and data governance to help the business make informed decisions across multiple plants and functions. The Senior Data Scientist leads and mentors a Data Scientist, establishes standards for analytical methods and communication, and serves as a trusted resource for resolving discrepancies between reports and determining the appropriate source of truth. This position also partners with engineering, finance, corporate development, and business leadership to develop production-ready analytical tools and models.

Essential Functions and 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.

Qualifications

Required Qualifications

• 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.

Preferred Qualifications

• 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.

Company Details:

• Location: Remote
• This position will report to the VP of AI & Analytics
  
  
  

Kreate is an equal opportunity employer. The Statements used herein are intended to describe the general nature and level of the work being performed by an employee in this position and are not intended to be construed as an exhaustive list of responsibilities, duties and skills required. Furthermore, they do not establish a contract for employment and are subject to change at the discretion of the Company.