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Synthetic Data Jobs (NOW HIRING)

Diverse Lynx

Healthcare Synthetic Data Architect

Chicago, IL · On-site

$65.75 - $84.50/hr

Diverse Lynx is seeking a Healthcare Synthetic Data Architect to build and enhance the synthetic data capabilities within the quality engineering organization. The role involves designing a clinical ...

Humana

Data Engineer, Synthetic Data Generation

Frisco, TX · On-site +1

$107K - $128K/yr

You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees ...

Humana

Data Engineer, Synthetic Data Generation

Frisco, TX · On-site +1

$107K - $128K/yr

You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees ...

Humana

Data Engineer, Synthetic Data Generation

Louisville, KY · On-site +1

$110K - $132K/yr

You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees ...

Humana

Data Engineer, Synthetic Data Generation

Louisville, KY · On-site +1

$110K - $132K/yr

You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees ...

Humana

Data Engineer, Synthetic Data Generation

Frisco, TX · On-site +1

$107K - $128K/yr

You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees ...

Nvidia

Build synthetic data generation pipelines using LLM-based methods and automated quality evaluation, producing datasets that improve the pre- and post-training of LLMs such as Nemotron - reasoning ...

Nvidia

Build LLM-based methods for synthetic data generation, privacy, and context-aware anonymization, with automated evaluation across multilingual text, documents, and multimodal content. * Optimize task ...

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Synthetic Data information

What is the highest paying data job?

In the field of synthetic data, senior roles such as Machine Learning Engineers, Data Scientists, and AI Researchers tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in programming, data modeling, and familiarity with AI tools and frameworks.

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 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 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.

Which 3 jobs will survive AI?

Synthetic Data roles, data scientists, and AI/ML engineers are expected to persist as AI advances because they involve designing, managing, and improving AI systems, which require specialized expertise. These jobs often require skills in programming, statistical analysis, and domain knowledge, making them less susceptible to automation. Continuous learning and staying updated with AI tools and frameworks are essential for long-term job security in these fields.

What is an example of synthetic data?

Synthetic data in the context of a synthetic data job involves artificially generated data that mimics real datasets, such as computer-generated images, text, or numerical information created using algorithms like generative adversarial networks (GANs). It is used to train machine learning models while preserving privacy and reducing bias. Skills in data modeling and familiarity with data generation tools are important for this role.

What is the salary of a synthetic data engineer?

The salary of a synthetic data engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in data modeling, programming, and machine learning tools like Python or TensorFlow tend to earn higher salaries.

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.
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What states have the most Synthetic Data jobs? States with the most job openings for Synthetic Data jobs include:
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Synthetic Data jobs near you
Infographic showing various Synthetic Data job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Healthcare Synthetic Data Architect

Healthcare Synthetic Data Architect

Diverse Lynx

Chicago, IL • On-site

$65.75 - $84.50/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Diverse Lynx is seeking a Healthcare Synthetic Data Architect to build and enhance the synthetic data capabilities within the quality engineering organization. The role involves designing a clinical synthetic data harness for AI solution testing and collaborating with various teams to create realistic test environments.
Responsibilities:
• Build the synthetic data sub-function within the quality engineering organization.
• Design a clinical synthetic data harness capable of supporting a “hospital twin” or simulated hospital environment for AI solution testing.
• Work with partners to bring Digital-twin and synthetic data generation capabilities that can be leveraged across programs and products.
• Create realistic and privacy-conscious test environments that allow AI teams to evaluate solutions safely before broader adoption.
• Collaborate with QA, engineering, and architecture teams to align simulation capabilities with AI use cases and maturity needs.
• Support iterative refinement of the framework through controlled test environments and high-fidelity synthetic data assets.
Qualifications:
Required:
• Strong background in synthetic data, data engineering, simulation, or healthcare data environments.
• Ability to translate quality goals into practical test environments and reusable validation assets.
• Familiarity with regulated healthcare data constraints and enterprise data governance considerations.
• Comfort working in a highly collaborative and evolving greenfield environment.
• Exp need – 10+ years
Company:
Diverse Lynx is a WBENC- and NMSDC-certified partner, helping organizations turn diversity goals into measurable impact through staffing and contingent workforce solutions. Founded in 2002, the company is headquartered in Princeton, New Jersey, US, , with a team of 1001-5000 employees. The company is currently Late Stage.
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About Diverse Lynx

Sourced by ZipRecruiter

Diverse Lynx, based in Princeton, NJ, US, is a reputable company in the Information Technology sector. The firm, as reflected through its website diverselynx.com, specializes in delivering comprehensive IT solutions. These solutions range from IT consulting to robust digital transformation strategies, IT staffing, and full-time placements services. The company was established in 2008, and it prides itself on providing simplified, efficient technology solutions designed to meet the unique needs of each client.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Princeton, NJ, US

Year founded

2002

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