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Synthetic Data Jobs in Ohio (NOW HIRING)

Business System Analyst

Columbus, OH · On-site

$85K - $100K/yr

Design and create synthetic or other test data sets to validate data pipelines, edge cases, and product logic. * Validate data outputs, pipeline changes, and releases to confirm accuracy and ...

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Synthetic Data information

What is synthetic data and how is it used?

Synthetic data refers to artificially generated information that mimics real-world data but does not contain any actual personal or sensitive details. It is commonly used to train machine learning models, test software, and protect privacy when sharing datasets. By using synthetic data, organizations can avoid data privacy concerns and still gain valuable insights or test algorithms effectively. This approach is especially valuable in industries like healthcare and finance where real data may be restricted. Synthetic data can be generated using various statistical techniques, simulations, or machine learning models.

What are the key skills and qualifications needed to thrive as a synthetic data engineer, and why are they important?

To thrive as a Synthetic Data Engineer, you need a strong background in computer science, statistics, and data modeling, usually with a degree in a related field. Experience with programming languages like Python or R, familiarity with machine learning frameworks, and knowledge of data privacy tools are essential. Strong analytical thinking, attention to detail, and effective communication help in designing robust data solutions and collaborating with stakeholders. These skills ensure the creation of high-quality synthetic datasets that support research, model training, and compliance with data privacy regulations.

What are the main challenges faced by professionals working with synthetic data in a production environment?

One of the primary challenges in a synthetic data role is ensuring that the generated datasets accurately reflect real-world scenarios while maintaining privacy and compliance standards. Professionals often need to balance data utility with the risk of introducing bias or unrealistic patterns. Collaboration with data scientists, engineers, and domain experts is essential to validate results and integrate synthetic data into machine learning pipelines. Additionally, staying updated on evolving tools and best practices is crucial for maintaining data quality and relevance.

What is the difference between Synthetic Data vs Data Analyst?

AspectSynthetic DataData Analyst
CredentialsNone required, but knowledge of data generation tools helpfulBachelor's degree in data science, statistics, or related field
Work EnvironmentData labs, software development teams, AI/ML projectsBusiness environments, analytics teams, reporting platforms
Industry UsageAI training, testing, privacy complianceData interpretation, reporting, decision support

While Synthetic Data involves creating artificial datasets for testing and training AI models, Data Analysts focus on interpreting real-world data to generate insights. Both roles require data literacy, but Synthetic Data specialists focus on data generation techniques, whereas Data Analysts analyze existing data to inform business decisions.

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

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

What cities in Ohio are hiring for Synthetic Data jobs?

Cities in Ohio with the most Synthetic Data job openings:

Infographic showing various Synthetic Data job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Lead Test Data Management Engineer

Huntington

Columbus, OH • On-site, Remote

Full-time

Posted 12 days ago


Huntington National Bank rating

8.1

Company rating: 8.1 out of 10

Based on 174 frontline employees who took The Breakroom Quiz

67th of 175 rated banks


Job description

Description The Lead Test Data Management Engineer is responsible for translating Huntington's Test Data Management (TDM) strategy into operational capabilities. This role serves as the bridge between architecture, engineering, governance, and delivery teams, driving the design, implementation, and adoption of enterprise test data capabilities that reduce reliance on production data in lower environments. The position combines technical leadership, solution design, and hands-on engineering expertise to establish repeatable test data services, accelerate pilot delivery, and create the foundation for a scalable Test Data Management capability.

Basic Qualifications: Bachelor's Degree 5+ years of related experience or an additional 4 years of related work experience may be considered in lieu of the Bachelor's Degree Platform & Capability Leadership Partner in defining the TDM roadmap and engineering priorities while providing technical leadership for implementation. Identify opportunities to eliminate production data usage in non-production environments. Provide analysis and recommendations for build-vs-buy evaluations, technology tradeoffs, and implementation decisions.

Engineering & Solution Delivery Design and implement synthetic data generation and test data provisioning solutions. Build reusable automation, data pipelines, engineering patterns, and accelerators. Integrate TDM capabilities with testing, quality engineering, and CI/CD processes.

Partner with application teams to onboard use cases and validate solutions. Evaluate and implement tooling to improve test data quality, availability, and efficiency. Maintain deep technical expertise in TDM tools, synthetic data technologies, and supporting platforms.

Test Data Lifecycle Management Define and operationalize end-to-end test data lifecycle processes. Establish repeatable provisioning, refresh, archival, and retirement patterns. Define service models for requesting, generating, delivering, and maintaining test data.

Data Quality, Reuse & Governance Establish reusable synthetic data patterns and data asset libraries. Develop standards for referential integrity and realistic test data creation. Define validation approaches to ensure synthetic data is fit for purpose.

Measure and report progress toward reducing or eliminating production data usage. Adoption & Organizational Enablement Support onboarding, training, and adoption activities across technology teams. Monitor emerging industry trends and recommend improvements to Huntington's TDM capabilities.

Establish reusable engineering patterns and operational processes that support future scalability. Additional Experience Experience designing and implementing technology or data solutions. Experience with databases, APIs, data pipelines, automation frameworks, and software delivery practices.

Demonstrated ability to lead complex technical initiatives across multiple teams and stakeholders. Experience with synthetic data generation, masking, tokenization, virtualization, or privacy-preserving data techniques. Experience implementing automated test data provisioning solutions.

Familiarity with Agile delivery models, DevOps practices, and CI/CD integration. Experience evaluating and implementing technology platforms and vendor solutions. Strong understanding of data governance, risk management, compliance, and information security principles.

Experience supporting large-scale application development and testing environments. Ability to balance strategic planning with hands-on technical execution. Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay) Yes Workplace Type: Office Our Approach to Office Workplace Type Certain positions outside our branch network may be eligible for a flexible work arrangement.

We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter.

Specific work arrangements will be provided by the hiring team. Huntington is an Equal Opportunity Employer. Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.

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