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Data Science Training Jobs in Ohio (NOW HIRING)

Visa Hunt

$165 - $234/hr

Data Science Expert Type: Contract Compensation: $120-$170/hour Location: Remote Role ... Prior experience with AI training, evaluation, or human‑data projects. #J-18808-Ljbffr

GRVTY

Data Science - Senior

Dayton, OH

Build and manage datasets for training and evaluation in collaboration with subject matter experts ... Advanced degree in Computer Science, Data Science, Electrical Engineering, or related field, or ...

Credence

Data Science Manager

Bath, OH · On-site

$100 - $140/hr

Position Summary Credence has an immediate need for a Data Science Manager at the journeyman level ... Training & Development #J-18808-Ljbffr

New

GRVTY

Data Science - Senior

Dayton, OH · On-site

Build and manage datasets for training and evaluation in collaboration with subject matter experts ... Advanced degree in Computer Science, Data Science, Electrical Engineering, or related field, or ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

... training on all major on-going Data Science and Analytics projects. When required, the Staff Data Scientist will also act as a project manager where vendors, suppliers and consultants are engaged on ...

Munich Re

Data Scientist

Akron, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Dayton, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Amelia, OH · On-site

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Cleveland, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Cincinnati, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Amelia, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Munich Re

Data Scientist

Columbus, OH · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... training can easily find connections to. Understand stakeholders' requests and hidden issues and ...

Kemper

Data Scientist

Cincinnati, OH · On-site +1

Data Science is a driver of significant competitive advantage for Kemper and is critical to the ... Solid understanding of statistical modeling and machine learning concepts, including model training ...

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Data Science Training information

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How much do data science training jobs pay per year?

As of Aug 30, 2026, the average yearly pay for data science training in Ohio is $95,051.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,902.00 and $112,437.00 per year, depending on experience, location, and employer.

What is data science training?

A Data Science Training job involves teaching and guiding individuals or teams in data science concepts, tools, and techniques. Trainers design curricula, conduct workshops, and provide hands-on experience with programming languages like Python or R, machine learning, and data visualization. They may work for educational institutions, corporate training programs, or independently to upskill professionals. The goal is to equip learners with the skills needed to analyze data, build models, and make data-driven decisions.

What are the typical responsibilities of a professional in data science training?

Individuals in Data Science Training roles are responsible for developing, organizing, and delivering curriculum on topics such as data analysis, machine learning, and data visualization. They often lead workshops, create interactive tutorials, and provide one-on-one guidance to learners from diverse backgrounds. Collaboration with data science teams and subject matter experts to ensure training content is current and industry-relevant is common. Additionally, professionals assess learner progress and adapt materials to continuously improve the educational experience. This role is ideal for those passionate about teaching and staying at the forefront of new data science advancements.

What are the key skills and qualifications needed to thrive in data science training, and why are they important?

To excel in Data Science Training roles, you need a solid foundation in data analysis, statistical modeling, and expertise with programming languages like Python or R, often supported by a degree in data science or a related field. Familiarity with tools such as Jupyter Notebooks, SQL, machine learning platforms, and certifications like Google Data Analytics or Microsoft Certified: Data Scientist Associate are highly valued. Excellent communication, patience, and instructional skills help convey complex topics clearly and foster a collaborative learning environment. These combined skills are essential for effectively designing and delivering training that empowers learners to succeed in the rapidly evolving field of data science.

How do I get a job in data science training with no experience?

To get a job in data science training with no experience, focus on building foundational knowledge through online courses, certifications, and practical projects. Developing strong communication skills and familiarity with tools like Python, R, or SQL can also improve your chances, and gaining experience through internships or volunteering can help demonstrate your abilities to employers.

What training do you need to be a data science training?

To become a data science trainer, you typically need a strong background in data science, including skills in programming languages like Python or R, statistical analysis, and machine learning. Relevant certifications, such as Certified Data Scientist or specialized training programs, can enhance credibility, and experience with data tools and platforms is often required. Continuous learning and staying updated with industry trends are also important for effective training.

What are the most commonly searched types of Data Science Training jobs in Ohio?

The most popular types of Data Science Training jobs in Ohio are:

What are popular job titles related to Data Science Training jobs in Ohio?

For Data Science Training jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Data Science Training jobs in Ohio look for?

The top searched job categories for Data Science Training jobs in Ohio are:

Data Science Training jobs near you
Infographic showing various Data Science Training job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 83% Physical, 1% Hybrid, and 16% Remote job distribution, with an average salary of $95,051 per year, or $45.7 per hour.

BN31P2-Data Scientist

Columbus, OH • On-site

Chemical Abstracts Service
See more jobs at Chemical Abstracts Serviceexternal

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 25 days ago

Job description

BN31P2- Data Scientist CAS Columbus, OH
CAS uses unparalleled scientific content, specialized technology and unmatched human expertise to help R&D organizations across Commercial, Government and Academic sectors create groundbreaking innovations that benefit the world. As the Scientific Information Solutions Division of the American Chemical Society, CAS manages the largest curated reservoir of scientific knowledge, and for 119 years, has helped innovators mine, assess and apply that information to keep businesses thriving. The CAS team is global, diverse, endlessly curious and strives to make actionable scientific insights accessible to innovators worldwide.
CAS is currently seeking a Data Scientist. This position will be located in our headquarters in Columbus, Ohio.
Job Summary
This is an individual contributor role on the Data Analytics and Insights (DAI) team, which builds the AI that powers CAS's scientific information products. As a data scientist, you will build the models, agents, and AI-powered features that ship in those products, working alongside data engineers, product managers, and scientific domain experts.
This role requires dual-domain expertise: you must be both a capable software engineer and formally trained in a scientific discipline relevant to CAS's customers (chemistry, life sciences, materials science, or a related field). DAI builds AI that is grounded in CAS's scientific content rather than layered on top of it, so the people who build it need to read the science as well as write the code. You will work on features such as the Newton research assistants in SciFinder and BioFinder, the natural-language query agent in IPFinder, predictive models that ship inside products (for example property, toxicity, or biologic developability prediction), and AI-assisted content curation pipelines, using your scientific training to judge whether their outputs are correct and useful to working scientists.
Success in this role requires strong programming fundamentals, formal scientific training, a genuine interest in agentic AI, and a collaborative approach to building reliable, production-grade systems. Candidates who bring only software engineering or only scientific training are not a fit for this position.
Job Accountability
  • Develop and deploy agent-based workflows, retrieval-augmented generation (RAG) pipelines, and LLM-powered features within CAS products using Python, LangGraph/LangChain, and related tools.
  • Develop and deploy machine learning models that ship inside CAS products (for example property, toxicity, or biologic developability prediction), using your scientific training to inform feature design and to validate model behavior.
  • Ground agentic and predictive features in CAS's authoritative scientific content, and use your scientific training to judge whether system outputs are accurate, defensible, and useful to researchers.
  • Engineer for production, not for demos: deliver clean, tested, well-documented software with appropriate safeguards such as content safety guardrails, entitlement-based access control, evaluation, and model fallback, following team engineering standards (unit, integration, and end-to-end tests, containerized development, and CI/CD practices).
  • Work with product managers, scientific domain experts, data engineers, and other teams to translate scientific and research requirements into working technical solutions.
  • Contribute to evaluation frameworks for GenAI systems, focusing on accuracy, reliability, scientific correctness, and continuous improvement of agentic features.
  • Build and operate solutions on cloud infrastructure (AWS, Azure, GCP, or similar), supporting the production deployment and ongoing operations of AI systems.
  • Use agentic software development tools such as Claude Code as a core part of the daily workflow to accelerate delivery and maintain quality.
  • Contribute to DAI's innovation and competitive-intelligence work by prototyping emerging AI capabilities and running structured experiments that test where AI can replicate or extend CAS capabilities.
  • Stay current with advances in generative AI and agentic architectures, and share knowledge with the team through demos, documentation, and internal learning sessions.

Required Qualifications
This role requires expertise in two domains. Both the scientific and the software engineering qualifications below are required, not alternatives.
Scientific domain
  • Bachelor's degree or higher in a scientific discipline relevant to CAS's customer domains (chemistry, life sciences, materials science, or a closely related field). This scientific training is a gating requirement for the role, not a preference.
  • The ability to read scientific content in your field and reason about it accurately enough to evaluate the outputs of AI systems that serve working scientists (for example, recognizing when a predicted property or a generated answer is wrong).

Software engineering and AI domain
  • 2+ years of professional experience in software engineering, applied machine learning, or data science, with demonstrated delivery of working systems.
  • Strong Python programming skills with solid software engineering fundamentals (version control, testing, code review, documentation).
  • Hands-on experience building applications with large language models, including agentic workflows, RAG, prompt engineering, or similar patterns.
  • Experience with or strong interest in agentic AI frameworks such as LangGraph, LangChain, or equivalent platforms.
  • Proficiency with agentic software development tools (e.g., Claude Code or similar AI-assisted development environments).
  • Experience deploying and operating software in at least one cloud environment (AWS, Azure, or GCP).

Both domains
  • Strong written and verbal communication skills, with the ability to work effectively in cross-functional teams that include both engineers and scientists.

Desired but Not Required
  • Graduate degree (M.S. or Ph.D.) in a scientific discipline relevant to CAS's customer domains, giving deeper command of the science behind the products.
  • Coursework, a second degree, or equivalent experience in Computer Science, Engineering, or Statistics that complements the scientific training.
  • Experience building and deploying predictive ML models in a scientific or regulated domain.
  • Experience with cloud AI/ML services and model hosting platforms.
  • Familiarity with containerized development workflows and API design.
  • Experience with evaluation frameworks for AI/ML systems, including accuracy, reliability, and cost optimization.

CAS offers a competitive salary and comprehensive benefits package, including a generous vacation plan, medical, dental, vision insurance plans, and employee savings and retirement plans. Candidates for this position must be authorized to work in the United States and not require work authorization sponsorship by our company for this position now or in the future. EEO/Disabled/Veteran
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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