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Data Annotation Tech Remote Jobs in Ohio (NOW HIRING)

FirstEnergy

Supervisor Data Engineering

Akron, OH · Remote

Position is currently remote but may work at or visit a facility based on business need. This ... Ensuring adherence to data engineering standards and governance, as well as IT change management ...

ALLOBAAS

Data Engineer II

Lakewood, OH · On-site +1

Stay informed on emerging data technologies and trends, sharing insights to help identify ... If fully remote: must be willing to travel * This position will require the ability to work ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate)   ... Coordinate with vendors, consultants, and technology partners when external expertise is required ...

dunnhumby

Senior Applied Data Scientist

Cincinnati, OH · On-site +1

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 ...

NTT DATA Services

Sales Executive III

Columbus, OH · Remote

$144K - $287K/yr

This is a remote position based in the greater Midwest area, with travel required for client ... NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune ...

NTT DATA Services

Sales Executive III

Columbus, OH · Remote

$144K - $287K/yr

This is a remote position based in the greater Midwest area, with travel required for client ... NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune ...

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Data Annotation Tech Remote information

What are the key skills and qualifications needed to thrive as a Data Annotation Tech (Remote), and why are they important?

To excel as a Data Annotation Tech (Remote), you need attention to detail, basic computer literacy, and familiarity with data labeling practices, often supported by a high school diploma or equivalent. Proficiency with annotation tools such as Labelbox, Supervisely, or proprietary platforms is typically required, and training in data privacy or quality assurance may be beneficial. Strong communication, time management, and the ability to focus independently are standout soft skills for this remote role. These competencies are crucial to ensure accurate, high-quality data labeling that directly impacts the effectiveness of AI and machine learning models.

What are some common challenges faced by remote Data Annotation Technicians, and how can they be addressed?

Remote Data Annotation Technicians often encounter challenges such as maintaining consistent annotation quality, managing repetitive tasks, and ensuring clear communication with team leads or project managers. To address these, it's helpful to establish a structured daily routine, use collaboration tools to stay connected with the team, and regularly review project guidelines to ensure accuracy. Many organizations also provide feedback loops and quality assurance checks, so being proactive in seeking feedback can help improve performance and job satisfaction.

What are Data Annotation Tech Remote jobs?

Data Annotation Tech Remote jobs involve working from home or another remote location to label, tag, or classify data such as text, images, audio, or video. This work is essential for training and improving artificial intelligence and machine learning models. Data annotators use specialized software tools to accurately identify and categorize data according to specific guidelines provided by employers. These roles require attention to detail, consistency, and sometimes subject-matter expertise, depending on the project. Remote data annotation jobs are popular because they often offer flexible schedules and the ability to work from anywhere.

What is the difference between Data Annotation Tech Remote vs Data Labeling Specialist?

AspectData Annotation Tech RemoteData Labeling Specialist
CredentialsBasic technical skills, sometimes certifications in data annotation toolsSimilar credentials, often with experience in labeling software
Work EnvironmentRemote, often freelance or contract-basedRemote or on-site, depending on employer
Industry UsageUsed across AI, machine learning, and data science companiesCommon in AI, autonomous vehicles, and tech firms

Both roles involve labeling data for machine learning models, with similar credentials and remote work options. The main difference lies in job titles used by employers, but their responsibilities and industry applications overlap significantly.

What are the most commonly searched types of Data Annotation Tech jobs in Ohio? The most popular types of Data Annotation Tech jobs in Ohio are:
What are popular job titles related to Data Annotation Tech Remote jobs in Ohio? For Data Annotation Tech Remote jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Annotation Tech Remote jobs in Ohio look for? The top searched job categories for Data Annotation Tech Remote jobs in Ohio are:
What cities in Ohio are hiring for Data Annotation Tech Remote jobs? Cities in Ohio with the most Data Annotation Tech Remote job openings:
Data Annotation Tech Remote jobs near you
Infographic showing various Data Annotation Tech Remote job openings in Ohio as of May 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Temporary. Highlights an 45% Physical, 6% Hybrid, and 49% Remote job distribution.
Lead Data Scientist - US Remote

Lead Data Scientist - US Remote

Hexion, Inc.

Columbus, OH • On-site, Remote

Full-time

Posted 7 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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