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Remote Science Communication Jobs in Ohio (NOW HIRING)

CSAA

Commercial Pricing Manager - Remote

Delaware, OH · Remote

... communicate analytical insights and recommendations. Your Work: * Develop and maintain business ... BA/BS in statistics, mathematics, actuarial science or related area and 5 years of post bachelor ...

Bread Financial

Data Scientist

Columbus, OH · On-site +1

$101K - $198K/yr

Job Summary The Data Science role at Bread Financial delivers best-in-class actionable business ... Communicate/Talking * Stationary Position/Seated * Typing/Writing * Focus and complete tasks in ...

A.C. Coy

Oracle Developer (Remote)

Columbus, OH · Remote

$54.50 - $67.75/hr

Bachelor's degree in computer science or equivalent training required. * 5+ years of Oracle related ... Excellent communication skills. * Ability to obtain a Position of Public Trust Clearance. * Must be ...

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Remote Science Communication information

What is the difference between Remote Science Communication vs Remote Science Writing?

AspectRemote Science CommunicationRemote Science Writing
Required CredentialsScience degrees, communication skills, possibly certifications in science communicationScience degrees, strong writing skills, possibly certifications in technical or scientific writing
Work EnvironmentVirtual, often involves multimedia, presentations, and public engagementPrimarily virtual, focused on creating written content like articles, reports, and manuals
Employer & Industry UsageResearch institutions, science media outlets, educational organizationsScientific publishers, research organizations, educational platforms
Search & Comparison IntentUnderstanding roles involving science communication and outreachLooking for scientific writing opportunities and content creation roles

Remote Science Communication focuses on conveying scientific concepts through various media and engaging audiences, while Remote Science Writing emphasizes creating written scientific content. Both roles require science backgrounds but differ in their primary output and communication methods.

What are the key skills and qualifications needed to thrive as a Remote Science Communicator, and why are they important?

To thrive as a Remote Science Communicator, you need a strong background in science, excellent writing or multimedia communication skills, and at least a bachelor's degree in a relevant field. Familiarity with digital communication tools, content management systems, and social media platforms is typically required, and certifications in science communication or digital marketing can be beneficial. Exceptional soft skills include creativity, adaptability, and the ability to translate complex scientific concepts into accessible language. These skills are crucial for effectively engaging diverse audiences and ensuring accurate dissemination of scientific information in a remote environment.

What is remote science communication?

Remote science communication involves sharing scientific information, research, and discoveries with diverse audiences using digital platforms, rather than in-person events. Professionals in this field may create content for websites, social media, podcasts, webinars, or virtual conferences, aiming to make complex scientific topics accessible and engaging. This role requires strong communication skills, science literacy, and the ability to use digital tools effectively. Remote science communicators often collaborate with researchers, educators, and media outlets from anywhere in the world.

What are some common challenges faced by professionals in remote science communication roles, and how can they be addressed?

One common challenge in remote science communication is ensuring clear and engaging messaging without face-to-face interaction, which can make it harder to gauge audience understanding. Collaborating across time zones and managing effective communication with scientists and stakeholders can also be complex. To address these, remote science communicators often rely on regular virtual meetings, collaborative tools, and clear documentation of project goals and feedback. Building a strong digital presence and adapting content for different online platforms are also key strategies for success in this role.
What are the most commonly searched types of Science Communication jobs in Ohio? The most popular types of Science Communication jobs in Ohio are:
What are popular job titles related to Remote Science Communication jobs in Ohio? For Remote Science Communication jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Science Communication jobs in Ohio look for? The top searched job categories for Remote Science Communication jobs in Ohio are:
What cities in Ohio are hiring for Remote Science Communication jobs? Cities in Ohio with the most Remote Science Communication job openings:
Remote Science Communication jobs near you
Lead Data Scientist - US Remote

Lead Data Scientist - US Remote

Hexion, Inc.

Columbus, OH • On-site, Remote

Full-time

Posted 10 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.

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