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Management Science Jobs in Ohio (NOW HIRING)

Air Force Materiel Command

$92K - $143K/yr

Qualifications Experience requirements are described in the Office of Personnel Management (OPM) Qualification Standards for General Schedule Positions, Professional and Scientific Positions. BASIC ...

Tri-C

Instructor, Upward Bound: Science

Cleveland, OH · On-site

$25.25/hr

Science Department: Youth, Adult and Community Connections Upward Bound Program Location ... Prog Mgr, Upward Bound (Trio) Recruitment Type: External/Internal Requisition ID: req7232 ...

Southern Rivers High School

Science Teacher

Van Buren, OH · On-site

$40/hr

SCIENCE TEACHER NOTE: ALL VACANCY POSTINGS ARE PENDING BOARD APPROVAL.NOTE: THREE REFERENCES MUST ... Efficiently manage instructional time.Effectively manage the behavior of learners for the integrity ...

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All JobsManagement Science JobsManagement Science Jobs in Ohio

Management Science information

See Ohio salary details

$23.3K

$46K

$75.1K

How much do management science jobs pay per year?

As of Sep 5, 2026, the average yearly pay for management science in Ohio is $46,005.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,600.00 and $49,400.00 per year, depending on experience, location, and employer.

What is management science?

Management science is an interdisciplinary field that uses analytical methods, such as mathematics, statistics, and computational techniques, to solve complex business and organizational problems. It aims to improve decision-making, efficiency, and productivity within organizations by applying quantitative approaches to management issues. Professionals in this field may work on optimizing supply chains, forecasting demand, resource allocation, and other areas where data-driven decisions are needed. Management science is widely used in industries like manufacturing, logistics, finance, healthcare, and government.

How does a management science professional typically collaborate with other departments within an organization?

Management Science professionals frequently work cross-functionally, collaborating with departments such as operations, finance, marketing, and IT. They apply quantitative analysis and modeling to solve complex business problems, often acting as a bridge between technical teams and business leaders. Effective communication and the ability to translate data-driven insights into actionable recommendations are key to success in this role. Regular meetings, joint project teams, and collaborative problem-solving sessions are common, making teamwork and adaptability essential skills.

What are the key skills and qualifications needed to thrive as a management science professional, and why are they important?

To thrive in Management Science, you need strong analytical skills, quantitative reasoning, and a background in mathematics, business, or related fields, often supported by a relevant degree. Familiarity with data analysis tools like Excel, R, Python, and optimization software, as well as certifications such as Six Sigma or PMP, is common. Exceptional problem-solving abilities, communication skills, and teamwork set top performers apart in this role. These skills are crucial for developing effective strategies and solutions that optimize organizational performance and decision-making.

What is the difference between Management Science vs Data Analyst?

AspectManagement ScienceData Analyst
Required CredentialsBachelor's or Master's in Management, Operations Research, or related fieldsBachelor's or Master's in Statistics, Data Science, or related fields
Work EnvironmentConsulting firms, corporate strategy departments, research institutionsBusiness, finance, marketing departments, or analytics firms
Employer & Industry UsageUsed in industries requiring optimization and decision modelingUsed across industries for data interpretation and reporting

Management Science focuses on applying quantitative methods to optimize decision-making and solve complex problems, often involving modeling and simulation. Data Analysts primarily interpret and visualize data to support business insights. While both roles require analytical skills, Management Science emphasizes operational research and strategic modeling, whereas Data Analysts focus on data collection, cleaning, and reporting.

Is management science still relevant today?

Management science remains highly relevant as it involves applying quantitative methods, data analysis, and modeling techniques to improve decision-making and operational efficiency in organizations. Professionals in this field often use tools like optimization, simulation, and statistical analysis to solve complex business problems, making their skills valuable across various industries.

What can I do with a management science degree?

A management science degree prepares individuals for roles such as management analyst, operations manager, supply chain analyst, or business consultant. It involves skills in data analysis, decision-making, and problem-solving, often utilizing tools like spreadsheets and statistical software to improve organizational efficiency.

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

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

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

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

What cities in Ohio are hiring for Management Science jobs?

Cities in Ohio with the most Management Science job openings:

Management Science jobs near you
Infographic showing various Management Science job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $46,005 per year, or $22.1 per hour.

BN31P2-Data Scientist

Chemical Abstracts Service

Columbus, OH • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 2 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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