Data Scientist

marmon; Carol Stream (IL); Hybrid; USD 110,000 - 160,000; Full time

Benefits offered by this job

Hybrid work schedule

Professional development

Job summary

Marmon Foodservice Technologies, Inc. is seeking a Data Scientist within the Commercial Analytics team in the United States.

You will partner with cross-functional teams to translate business questions into advanced analytical, ML, and GenAI-enabled solutions that drive growth and profitability across pricing, lifecycle, and GTM decisioning. The role emphasizes data integration from multiple sources, building predictive and optimization models, and delivering decision-ready insights through

Qualifications

• Strong foundation in statistics and quantitative analysis.
• Experience with GenAI and agent-based AI concepts.
• Proficiency in Power BI and data storytelling.
• Ability to translate data insights into business recommendations.

Responsibilities

• Translate business questions into analytical, ML, and AI solutions.
• Design and automate models for forecasting and segmentation.
• Collaborate with IT/data engineering to deploy pipelines.
• Present findings via dashboards and executive briefs.

Skills

Statistics

Machine Learning

GenAI / AI

Power BI

Data Visualization

Data Engineering

Business Analytics

Tools

Copilot for M365

Copilot Studio

Azure AI

Azure Machine Learning

Power BI

Microsoft Fabric

Job description

Marmon Foodservice 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.

About the Job

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.

What You'll Do

• 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.

Who You Are

• 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.

Skills / Experience We're Looking For

• Ability to design analytical approaches that align with business objectives, constraints, and success metrics.
• Strong foundation in statistics, probability, and quantitative analysis, including descriptive and inferential techniques.
• Familiarity with Generative AI and agent-based AI concepts and their application to business analytics and decision support. Hands‑on usage of Microsoft Copilot tools (e.g., Copilot for M365, Copilot Studio, or embedded Copilot experiences) to accelerate analysis, code generation, and insight synthesis, and embed AI‑assisted analytics into business workflows
• Experience working within the Microsoft data (Fabric, PowerBI) and AI stack (Azure AI, Azure Machine Learning, AI Foundry)
• Proficiency in data visualization and storytelling using Power BI, others.
• Experience working with