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Synthetic Data Jobs (NOW HIRING)

Argyllinfotech

Test Data Architect

Minneapolis, MN · On-site

$66.50 - $85.50/hr

Design reusable test data patterns including data provisioning, data masking, synthetic data, and environment refresh. Understand and analyze ER diagrams, schemas, data dictionaries, data flows ...

Aptive

Data Scientist, Senior

Apply supervised, unsupervised, and reinforcement learning techniques to develop and evaluate data models specific to the healthcare domain, including work with synthetic data models and patient ...

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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.

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Synthetic Data jobs near you
Infographic showing various Synthetic Data job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Lead - Biomedical Data Factory Team

MUSC Health & Medical University of SC

Charleston, SC • On-site

Full-time

Re-posted yesterday

MUSC Health rating

7.0

Company rating: 7.0 out of 10

Based on 202 frontline employees who took The Breakroom Quiz

421st of 898 rated healthcare providers

Job description

Job Description Summary
The Lead of the Clinical Data Factory supports the data ecosystem that powers MUSC's AI development workflows. This role ensures PI/PHI-compliant synthetic data pipelines, model-training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major changes for continued workflow. The Lead works closely with Central IS Architecture and Security, and the AI Center to maintain an emergent AI architecture that reduces load on central IT while enabling rapid experimentation and compliant model development.
Entity
University Medical Associates (UMA) Only Employees and Financials
Worker Type
Employee
Worker Sub-Type
Classified
Cost Center
CC005532 EVPAA - Center for Artificial Intelligence
Pay Rate Type
Salary
Pay Grade
Health-34
Scheduled Weekly Hours
40
Work Shift
Job Description
Primary Areas of Responsibility (with % Allocation)
1. Synthetic Data Pipeline Management & Compliance - 40%
  • Maintain high-performance data pipelines meeting PI/PHI compliance standards.
  • Audit, monitor, and improve data quality, performance, and lineage.
  • Support model-training workflows with high-integrity synthetic datasets.
  • Ensure operational compliance, and follow through with IS Strategies and Approaches

2. System Architecture, Maintenance & Enhancement - 25%
  • Oversee lifecycle maintenance of AI Center Built Tools, patching, and upgrades to mini data infrastructure.
  • Partner with enterprise architecture teams to ensure alignment with evolving systems.
  • Communicate risks, dependencies, and required enhancements proactively.

3. Team Leadership & Technical Guidance - 20%
  • Lead and mentor Jr. Data Engineers and Jr. Architects.
  • Maintain documentation, operational workflows, and technical standards.
  • Coordinate team activities to meet service and uptime commitments.

4. Integration with AI Project Teams - 10%
  • Collaborate with AI Strategy & Ops, Research and AI Incubation teams to ensure data needs are met.
  • Provide technical support for data provisioning, synthetic layering, and model experimentation for the AI Center activities.

5. Governance, Quality & Model Integrity Support - 5%
  • Maintain data governance practices that support ethical model development.
  • Support model integrity monitoring and data risk mitigation in conjunction w/IS Guidance and Policy

Key Annual Performance Objectives
  • Meet synthetic data KPIs for quality, performance, and service uptime.
  • Reduce dependency on core IT architecture for AI model development.
  • Maintain compliance and operational stability of the synthetic data ecosystem.

Additional Job Description
Required Qualifications
  • Education: Master's degree required.
  • Experience: 2-3 years of relevant experience with some leadership exposure, ideally in data engineering, architecture, synthetic data systems, or compliant data environments.
  • Technical Capability: Experience in data engineering, synthetic data pipelines, ETL/ELT workflows, or regulated healthcare data systems.
  • Compliance Knowledge: Familiarity with PI/PHI handling, HIPAA, or regulated-data architectures preferred.
  • Leadership: Ability to mentor junior engineers/architects and coordinate technical backlog or system maintenance cycles.

If you like working with energetic enthusiastic individuals, you will enjoy your career with us!
The Medical University of South Carolina is an Equal Opportunity Employer. MUSC does not discriminate on the basis of race, color, religion or belief, age, sex, national origin, gender identity, sexual orientation, disability, protected veteran status, family or parental status, or any other status protected by state laws and/or federal regulations. All qualified applicants are encouraged to apply and will receive consideration for employment based upon applicable qualifications, merit and business need.
Medical University of South Carolina participates in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For further information about the E-Verify program, please click here: http://www.uscis.gov/e-verify/employees

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About MUSC Health

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MUSC is located in Charleston, SC, frequently named one of the best places in America to live. If charming, historic, vibrant, cultural, and coastal are adjectives that you find appealing, it's all here. In Charleston, you might find yourself dining at a world class restaurant tonight and relaxing on a boat as you explore our many waterways tomorrow. You might stroll along cobblestone streets, amidst centuries old homes by day and attend a jazz concert by night. Charleston is a place where you can live your life to its fullest.

Industry

Hospitality services

Company size

10,000+ Employees

Headquarters location

Charleston, SC, US

Year founded

1824

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