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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Marmon Foodservice Technologies, Inc. - **Location:** United States (Remote available) - **Salary:** $80,000.0 - $120,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, Cloud Computing, Code Generation, Customer Data Management, Data Cleansing, Information Engineering, Data Visualization, Data Warehousing, Database Queries, Decision Support Systems, Python (Programming Language), Machine Learning, Microsoft Data Access Components, Pattern Recognition, Power BI, Azure Machine Learning, Feature Engineering, Microsoft Power Automate, Generative AI, Pandas, Scikit Learn, Information Technology, Data Analytics, Virtual Agents - **Published:** July 14, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/p48zui9cbp ## About the Role * 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 real world, imperfect datasets and applying sound data preparation and feature engineering techniques. * Experience with MS Azure or MS Fabric being a plus, or any cloud-computing environment. * Strong written, verbal, and presentation skills with the ability to influence decision makers., * Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field. Master's Degree holders encouraged. * Advanced proficiency in Python for data analysis, modeling, and automation. Strong experience building and validating machine learning models using Python/R and libraries such as pandas, scikit-learn, or equivalent. * Strong SQL skills for querying, joining, and optimizing large relational datasets * Experience in data-driven analytics or data science roles, applying quantitative methods to business problems and translating business requirements into analytical solutions. ## Description 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. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)