Data Scientist

Marmon Food service Technologies, Inc. As a part of the global industrial organization Marmon Holdings—which is backed by Berkshire Hathaway—you’ll be doing things that matter, leading at every level, and winning a better way. We’re committed to making a positive impact on the world, providing you with diverse learning and working opportunities, and fostering a culture where everyone’s empowered to be their best.

This role is a core contributor within the Commercial Analytics organization, supporting enterprise-level decision making across pricing, equipment lifecycle performance, customer behavior, and commercial strategy. The Data Scientist partners closely with Commercial Analytics leadership and cross-functional stakeholders to convert business questions into advanced analytical, machine learning, and AI-enabled solutions. By combining strong quantitative rigor with the ability to translate insights into practical recommendations, this role strengthens the Commercial Analytics function’s mandate to deliver scalable, decision-ready intelligence that drives growth, profitability, and continuous improvement across the commercial lifecycle.

This role plays a critical part in advancing analytics across pricing, service/aftermarket, and go-to-market (GTM) decisioning. By integrating commercial, operational, and customer data, this role enables a more connected, end-to-end view of the commercial lifecycle—supporting data-driven decisions across acquisition, utilization, service, and replacement. This role is subject to our hybrid work model: we collaborate in the office on Monday, Tuesday, and Thursday.

The rest of the week, you have flexibility to work wherever it suits you best.

• Translate business requirements into analytical, machine learning, and GenAI / Agentic AI solutions, ensuring outputs are decision-ready, actionable, and accurate.
• Integrate and analyze large, complex datasets from multiple disparate internal and external sources, ensuring data quality, consistency, and analytical rigor.
• Design and automate predictive, explanatory, and optimization models, including forecasting, segmentation, and scenario modeling.
• Partner with stakeholders to define KPIs, success metrics, and measurement frameworks that align analytics with business outcomes.
• Develop and test project-specific data engineering pipelines via API inputs, ingestion/clean-up scripts, for use in visualizations and explanatory, predictive, and optimized models.
• Act as key SME partner for IT Data Engineering team to seamlessly hand-off proposed pipeline structure for inclusion in enterprise Data Lake/Data Warehouse as needed.
• Develop, deploy, and maintain statistical, machine learning, and AI-enabled models to solve business problems across pricing, lifecycle performance, customer behavior, operations, and commercial strategy.
• Leverage generative AI and agent-based approaches to accelerate insight generation, pattern detection, and analytical workflows.
• Communicate complex analytical findings clearly through dashboards, visualizations, and executive level presentations using tools such as Power Bi or similar platforms.
• Collaborate with analytics, data engineering, and business teams to continuously improve analytical systems, models, and processes.

• Business Translator:
  You can bridge technical depth and business context, converting data science outputs into clear recommendations.
• Innovative Thinker:
  You seek out new tools, methods, and AI-enabled approaches to improve insight generation and decision‑making.
• Quick Learner:
  You rapidly absorb new concepts and technologies, adapting easily to changing environments and priorities.
• Collaborative Partner:
  You work effectively across functions and communicate confidently with technical and non‑technical audiences.
• Self‑Directed:
  You take ownership of problems end‑to‑end and continuously look for opportunities to improve models, processes, and outcomes.
• Analytical and Quantitative:
  You bring strong statistical, mathematical, and problem‑solving skills to complex and ambiguous business questions.

• Ability to design analytical approaches that…