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Associate Data Scientist Jobs in Ohio (NOW HIRING)

The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings ... Bachelor's degree in computer science, math, statistics, or related field and internship experience ...

Weed Scientist

Marysville, OH · On-site

$77K - $90K/yr

Associates are expected to participate in our business segment as a hands-on researcher so that ... data analysis, and preparation of reports to be used to support product claims for regulatory ...

Showing results 41-60

Associate Data Scientist information

See Ohio salary details

$54.7K

$64.7K

$122.6K

How much do associate data scientist jobs pay per year?

As of Aug 18, 2026, the average yearly pay for associate data scientist in Ohio is $64,684.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,100.00 and $56,600.00 per year, depending on experience, location, and employer.

What does an associate data scientist do?

An Associate Data Scientist supports data-driven decision-making by collecting, cleaning, and analyzing large datasets. They use statistical methods and programming languages like Python or R to identify trends, build predictive models, and generate insights for business problems. Working under the guidance of more experienced data scientists, they also help visualize data and communicate findings to technical and non-technical stakeholders. This entry-level role often involves learning new tools and techniques while contributing to real-world projects.

What does an associate data scientist do?

The duties of an associate data scientist are to analyze statistical data analysis on large sets and identify trends by using advanced mathematical and computer science skills. Their responsibilities often include assisting in the production of statistical models, tools, and processes. They typically are in the process of pursuing a master’s degree and report to a senior data scientist. The qualifications you need are a bachelor’s degree in statistics, computer science, or a related field as well as experience working with machine-learning and data mining algorithms.

What are some typical projects an associate data scientist might work on, and how do they collaborate with other team members?

As an Associate Data Scientist, you can expect to contribute to a range of projects such as developing predictive models, analyzing large datasets to uncover business insights, and supporting the deployment of machine learning solutions. Collaboration is key; you'll often work closely with data engineers to prepare and process data, as well as with business analysts and product managers to align your findings with organizational goals. Regular meetings, code reviews, and knowledge-sharing sessions are common, providing opportunities to learn from senior data scientists and broaden your technical skills.

What are the key skills and qualifications needed to thrive as an associate data scientist, and why are they important?

To thrive as an Associate Data Scientist, you need strong analytical skills, a solid foundation in statistics, and proficiency in programming languages like Python or R, typically supported by a degree in a quantitative field. Experience with data visualization tools (e.g., Tableau), machine learning libraries (e.g., scikit-learn), and database systems (e.g., SQL) is often required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating data insights into actionable business solutions. These skills and qualities are essential for extracting valuable insights from complex data and driving data-informed decision-making within organizations.

What is the difference between Associate Data Scientist vs Data Analyst?

AspectAssociate Data ScientistData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; certifications like Microsoft Excel or Tableau are common
Work EnvironmentCollaborates with data science teams, develops models, and analyzes complex datasetsPrepares reports, visualizes data, and provides insights for decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms focusing on predictive modelingCommon across various industries for business reporting and operational analysis

The Associate Data Scientist typically focuses on building models and advanced analytics, requiring programming skills and statistical knowledge. Data Analysts mainly interpret data through reports and visualizations, often with less emphasis on coding. Both roles are essential in data-driven organizations but differ in technical depth and responsibilities.

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

The most popular types of Data Scientist jobs in Ohio are:

What cities in Ohio are hiring for Associate Data Scientist jobs?

Cities in Ohio with the most Associate Data Scientist job openings:

What are popular job titles related to Associate Data Scientist jobs in OH?

For Associate Data Scientist jobs in OH, the most frequently searched job titles are:

Infographic showing various Associate Data Scientist job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $64,684 per year, or $31.1 per hour.

Associate Data/ Metadata Analyst

Online Computer Library Center

Dublin, OH • On-site

Other

Medical, Retirement

Posted 4 days ago


Job description

Together we make breakthroughs possible.
At OCLC, we build technology with a purpose: to connect libraries and make knowledge accessible worldwide, because we believe that what is known must be shared. Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and other technologies that connect people and organizations to the information they need. We value the power of unique perspectives and experiences to unlock innovation. At OCLC, your ideas matter, whether you have two years of experience or 20. You'll learn, create, and problem-solve with technologists, product developers, librarians, researchers, marketing pros, and support teams around the world.
Why join OCLC?
OCLC is consistently recognized as a best place to work by several independent programs. We recognize and reward people and results with a comprehensive Total Rewards package. This means competitive compensation that reflects your unique contributions-performance, experience, and skills-along with exceptional benefits, including best-in-class health coverage, retirement plans with generous company contributions, and a commitment to your overall well-being.
  • We know the best ideas don't always happen at a desk. Take a walking meeting around our 100-acre campus or enjoy lunch on the patio. We're committed to your success-both personally and professionally. Hybrid work environment: For many roles, three days a week on-site, with occasional additional days based on business needs.
  • Free use of our on-site fitness center, gym sports, group exercise classes, and game room
  • Onsite catering and cafeteria subsidized by OCLC
  • Health and wellness events
  • Work environments with individual and team spaces and the latest technology tools
  • Paid parental leave and adoption assistance
  • Tuition reimbursement and Public Service Loan Forgiveness eligibility
  • Company-subsidized pricing on local tickets and memberships

Join us in transforming how people everywhere access information and be part of a mission-driven team that makes a global impact.
The job details are as follows:
The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings data, ensuring accuracy and integrity through evaluation, transformation, and maintenance. This entry-level role combines metadata expertise with developing technical skills in scripting, automation, and AI-assisted workflows. Working under regular supervision, the Associate will transition from executing well-defined tasks to taking ownership of complex data projects. This is an opportunity to develop expertise at the intersection of library data, modern data engineering, and emerging AI - in a team that invests in the growth of its people.
Responsibilities:
Data Operations & Quality
  • Data Lifecycle Management: Perform data ingest, normalization, enrichment, and matching according to established standards (e.g., MARC, KBART).
  • Quality Assessment: Profile incoming data to identify and resolve structural issues, encoding errors, and tagging discrepancies.
  • Troubleshooting: Investigate and resolve data quality issues, escalating complex problems to senior staff as needed.
  • Vendor Communication: Coordinate with external data providers and partner institutions regarding routine data specifications and quality issues.
Technical Solutions & Automation
  • Pipeline Support: Apply existing scripts and automated workflows to process data; identify inefficiencies and suggest process improvements.
  • Data Visualization: Use and interpret dashboards (e.g., Power BI) to monitor data quality trends and communicate findings.
  • AI Integration: Utilize AI-assisted tools for record matching and field mapping; contribute structured feedback that helps improve AI model accuracy over time.
Collaboration & Documentation
  • Knowledge Management: Document data source profiles, processing decisions, and technical workflows to ensure team-wide knowledge sharing.
  • Team Support: Execute foundational tasks to support senior analysts and participate in platform improvement projects.

Minimum Required Knowledge, Skills and Experience:
  • Bachelor's degree in computer science, math, statistics, or related field and internship experience with data analysis or creation of library data.
  • Entry-level analytical and communication skills, with attention to data quality while working under regular supervision.

Preferred Knowledge, Skills and Experience:
  • Metadata Standards: Foundational knowledge of MARC, Dublin Core, KBART, or BIBFRAME.
  • Technical Tools: Exposure to scripting languages (Python, SQL, or XSLT) and data transfer protocols (SFTP, APIs, or AWS S3).
  • Data Platforms: Conceptual familiarity with cloud data stores (e.g., Snowflake) and visualization tools (e.g., Power BI, Streamlit).
  • Emerging Tech: Interest in applying AI and linked data concepts (e.g., Schema.org) to library data challenges.

Working Conditions: Normal office environment.
ADA/EAA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.