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Remote Manufacturing Data Scientist Jobs in Ohio

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position Summary: The Staff Data Scientist will be a key role in the Data Science and Analytics team tasked ...

Location Remote in Europe. Albatross At Albatross, we're building the second pillar of AI: a ... The Role As a Data Scientist, you will design and deploy machine learning models that power real ...

Best-in-class engineering, design and manufacturing combined with category-leading brands in ... As a Senior Data Scientist, You Will * Apply machine learning, econometrics, and emerging AI ...

May telecommute 100% of the time from their home office, consistent with dunnhumby's remote work ... Deploy data science algorithms and market products on chosen tech stack for efficient and cost ...

... as manufactured homes and specialty dwellings - and the recreational market, including boats ... We are looking for a data scientist with proven expertise in executing AI/ML strategy, developing ...

... as manufactured homes and specialty dwellings - and the recreational market, including boats ... We are looking for a data scientist with proven expertise in executing AI/ML strategy, developing ...

... as manufactured homes and specialty dwellings - and the recreational market, including boats ... We are looking for a data scientist with proven expertise in executing AI/ML strategy, developing ...

... as manufactured homes and specialty dwellings - and the recreational market, including boats ... We are looking for a data scientist with proven expertise in executing AI/ML strategy, developing ...

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Remote Manufacturing Data Scientist information

What are the key skills and qualifications needed to thrive as a Remote Manufacturing Data Scientist, and why are they important?

To thrive as a Remote Manufacturing Data Scientist, you need expertise in data analytics, statistical modeling, and a solid educational background in fields like computer science, engineering, or statistics. Familiarity with programming languages (such as Python or R), machine learning platforms, and manufacturing-specific systems like ERP or MES is typically required. Strong problem-solving skills, attention to detail, and effective remote communication are essential soft skills for collaborating with cross-functional teams. These competencies enable you to extract actionable insights from complex manufacturing data, driving process improvements and operational efficiency from a remote setting.

How does a Remote Manufacturing Data Scientist typically collaborate with onsite engineering and production teams?

As a Remote Manufacturing Data Scientist, collaboration with onsite teams is often facilitated through regular virtual meetings, shared dashboards, and collaborative project management tools. You may analyze production data, develop predictive models, and then present insights and recommendations to engineers and plant managers via video calls or detailed reports. Building strong communication skills and familiarity with digital collaboration platforms is essential for bridging the gap between remote analytics and hands-on manufacturing processes. Proactively seeking feedback and clarifying technical requirements with onsite teams ensures your data-driven solutions are both practical and impactful.

What does a Remote Manufacturing Data Scientist do?

A Remote Manufacturing Data Scientist analyzes large sets of manufacturing data to uncover insights, optimize processes, and support decision-making, all while working offsite. They use statistical methods, machine learning, and data visualization tools to identify patterns, predict equipment failures, and recommend improvements for efficiency and quality. Collaborating with engineering and production teams, they help implement data-driven solutions without being physically present at the manufacturing facility. Their work contributes to reducing costs, improving productivity, and ensuring product quality in the manufacturing sector.

What is the difference between Remote Manufacturing Data Scientist vs Remote Manufacturing Engineer?

AspectRemote Manufacturing Data ScientistRemote Manufacturing Engineer
Required CredentialsDegree in Data Science, Statistics, or related field; proficiency in data analysis toolsDegree in Mechanical, Industrial, or Manufacturing Engineering; technical skills in manufacturing processes
Work EnvironmentPrimarily analytical, working with data sets and software tools remotelyFocus on process design, optimization, and technical implementation, often involving remote collaboration
Industry UsageUsed across manufacturing sectors for data-driven decision makingApplied in designing and improving manufacturing systems and processes

The main difference is that a Remote Manufacturing Data Scientist focuses on analyzing manufacturing data to inform decisions, while a Remote Manufacturing Engineer concentrates on designing and optimizing manufacturing processes. Both roles may work remotely and require technical expertise, but their core responsibilities differ significantly.

What are the most commonly searched types of Manufacturing Data Scientist jobs in Ohio? The most popular types of Manufacturing Data Scientist jobs in Ohio are:
What are popular job titles related to Remote Manufacturing Data Scientist jobs in Ohio? For Remote Manufacturing Data Scientist jobs in Ohio, the most frequently searched job titles are:
What cities in Ohio are hiring for Remote Manufacturing Data Scientist jobs? Cities in Ohio with the most Remote Manufacturing Data Scientist job openings:

Lead Data Scientist - US Remote

Hexion Careers

Columbus, OH • On-site, Remote

Full-time

Posted 2 days ago


Job description

Company Overview
 

Imagine Everything. Build the Future with Hexion.

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future.

This is where bold thinkers, problem-solvers, and innovators come together to shape what’s next. Whether you're engineering advanced materials, transforming manufacturing technologies, or leading strategic innovation, your ideas and actions leave a lasting mark. We cultivate an inclusive culture of growth, collaboration, and accountability, ensuring every contribution propels us forward.

We don’t follow the status quo—we challenge it, disrupt it, and improve it. Every role at Hexion is part of something bigger.

We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Your Future Starts Here.  

If you’re ready to push limits, reimagine what’s possible, and create the extraordinary, Hexion is where you belong. 

Anything is possible when you imagine everything. 

Job Responsibilities
  • Lead complex data science and machine learning initiatives supporting supply chain, manufacturing operations, capacity planning, demand forecasting, and operational decision-making. 
  • Design, develop, and own advanced ML solutions — including predictive models, time-series forecasting, optimization, and decision-support systems — scoped to supply chain and manufacturing use cases. 
  • Build, train, evaluate, and interpret machine learning models (regression, classification, clustering, forecasting) to quantify supply chain drivers, surface optimization opportunities, and improve operational outcomes. 
  • Develop and operationalize analytics and ML solutions using Databricks (Python / SQL / PySpark) for large-scale data processing, model development, and experimentation. 
  • Design and build multi-agent AI systems — including orchestrator-executor architectures, tool-calling agents, and RAG-based decision support — using frameworks such as Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph. 
  • Implement and extend solutions using the MCP to enable AI agents to access and act on enterprise data systems in supply chain and manufacturing contexts. 
  • Apply data science best practices including feature engineering, model validation, performance monitoring, reproducibility, and documentation. 
  • Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT to translate ambiguous business problems into structured ML and AI approaches. 
  • Develop and maintain self-service, automated, and AI-enabled analytics workflows that reduce manual effort and improve decision latency. 
  • Leverage Azure AI Foundry, Microsoft Copilot Studio, and Microsoft 365 Copilot extensibility to prototype and deploy AI-powered analytics and agent-based decision-support tools. 
  • Produce executive-ready insights through clear storytelling, visualizations, and recommendations using Power BI or embedded analytics. 
  • Set technical direction, establish reusable ML and AI frameworks, and mentor junior and mid-level data scientists across the team. 
  • Ensure high standards of data quality, governance, model validation, and explainability. 
Minimum Qualifications

Education & Experience (one of the following): 

  • Master’s degree in Statistics, Mathematics, Industrial Engineering, Data Science, Computer Science, Engineering, or a related quantitative field with 5+ years of relevant data science/analytics experience, OR 
  • Bachelor’s degree in the same or related fields with 8+ years of relevant data science / analytics experience. 


Technical: 

  • Demonstrated track record delivering advanced ML and data science solutions in supply chain, manufacturing, or industrial domains. 
  • Strong hands-on experience with machine learning and statistical modeling — development, interpretation, and operational business application. 
  • Strong proficiency in Databricks (Python, SQL, PySpark, Delta Lake). 
  • Hands-on experience with the MCP — building or consuming MCP servers/clients to connect AI agents to enterprise data systems, APIs, or ERP modules. 
  • Hands-on experience with multi-agent system design — architecting multi-agent systems using AutoGen, Semantic Kernel, LangChain/LangGraph, or Azure AI Agent Service; orchestrator-executor patterns, tool calling, memory management, and agent coordination. 
  • Compulsory — must have hands-on experience with one or more of the following: 
    • Azure AI Foundry 
    • Microsoft Copilot Studio 
    • Microsoft 365 Copilot extensibility 
    • Microsoft Power Platform (Power Automate, Power BI) 
  • Ability to translate complex business problems into ML / AI solutions and communicate findings to both technical and executive audiences. 
  • Strong stakeholder management and cross-functional collaboration skills. 
Preferred Qualifications
  • Experience operationalizing ML models into production in supply chain or manufacturing environments. 
  • Familiarity with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, PM, SD). 
  • Strong Power BI experience — semantic modeling, performance optimization, executive dashboard design. 
  • Exposure to MLOps on Azure (Azure ML, MLflow, Databricks Asset Bundles, CI/CD for analytics artifacts). 
  • Experience designing operational KPI frameworks (MAPE, OTIF, service level, OEE, downtime). 
  • Experience with statistical / simulation methods (Monte Carlo, scenario analysis, sensitivity analysis) applied to operations and supply chain. 
  • Familiarity with Palantir Foundry (pipelines, ontology, Workshop, AIP). 
  • Proven experience mentoring data scientists or leading end-to-end analytics initiatives. 
  • Familiarity with cloud-native data architectures and governed data platforms. 
Other
 

We are an Equal Opportunity, Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to gender, pregnancy, race, national origin, religion, age, sexual orientation, gender identity, veteran or military status, status as a qualified individual with a disability or any other characteristic protected by law.

To be considered for this position candidates are required to submit an application for employment through our career site and, be at least 18 years of age.  Any offer of employment will be conditioned upon successful completion of a drug test and background investigation, as well as authorization for the Company to conduct additional periodic background checks as required by the Chemical Facility Anti-Terrorism Standards (CFATS) or regulations adopted by the department of Homeland Security or other regulatory agencies. A prior criminal record is not an automatic bar to employment, and the Company will conduct an individualized assessment and reassessment, consistent with applicable law, prior to making any final employment decision.