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Clinical Data Programmer Jobs in Chicago, IL (NOW HIRING)

Sr. Healthcare Data Engineer

Chicago, IL · On-site +1

$109K - $149K/yr

Senior Healthcare Data Engineering Consultant - Our client is seeking a senior, hands-on Healthcare Data Engineering Consultant to design, build, and operationalize secure clinical-data de ...

Data Architect, Clinical

Chicago, IL · On-site

$65.75 - $84.50/hr

Required : • Bachelor's degree in computer science, Data Engineering, Information Systems ... clinical trials data, or other patient-centered data platforms. • Demonstrated experience ...

Experience with CDISC standards (SDTM/ADaM) as they relate to downstream SAS programming ... As an experienced Clinical Data AMS Senior Consultant you will have the ability to share new ideas ...

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... that drives clinical innovation and offers a path towards better patient outcomes. This is ... You'll work closely with data scientists, product teams, and other engineers to ensure that our ...

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Clinical Data Programmer information

See Chicago, IL salary details

$71.7K

$122.6K

$218.6K

How much do clinical data programmer jobs pay per year?

As of Aug 27, 2026, the average yearly pay for clinical data programmer in Chicago, IL is $122,645.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,500.00 and $185,600.00 per year, depending on experience, location, and employer.

What is a clinical data programmer?

Clinical Data Programmers are professionals who manage, process, and analyze clinical trial data using specialized programming languages and software. They are responsible for creating and validating programs that ensure data collected during clinical studies is accurate, consistent, and ready for statistical analysis. Their work is essential to the integrity of clinical research, enabling regulatory submissions and supporting medical decision-making. Clinical Data Programmers often work closely with clinical data managers, statisticians, and other clinical research professionals.

How does a clinical data programmer typically collaborate with clinical research teams during a study?

Clinical Data Programmers work closely with clinical research associates, data managers, biostatisticians, and project managers to ensure the integrity and accuracy of clinical trial data. They often participate in study setup meetings, provide input on case report form (CRF) design, and develop programs for data validation and cleaning. Regular communication is essential to resolve any discrepancies or issues that arise during data collection and to implement mid-study changes. This collaborative environment ensures that the data is reliable and meets regulatory requirements.

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

To thrive as a Clinical Data Programmer, you need a strong background in programming (especially SAS or SQL), understanding of clinical trial data, and a degree in life sciences, statistics, or a related field. Familiarity with electronic data capture systems, CDISC standards (SDTM/ADaM), and regulatory requirements is typically expected, and relevant certifications can be advantageous. Attention to detail, analytical thinking, and effective communication are essential soft skills for ensuring data integrity and collaborating with cross-functional teams. These skills and qualifications are vital for producing accurate, regulatory-compliant datasets that support clinical research and successful drug development.

What is the difference between Clinical Data Programmer vs Clinical Data Analyst?

AspectClinical Data ProgrammerClinical Data Analyst
Required CredentialsBachelor's in Life Sciences, Biostatistics, or related field; knowledge of programming languages like SAS or RBachelor's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentClinical trial data management teams, often in CROs or pharmaceutical companiesData analysis teams, often in healthcare or research organizations
Employer & Industry UsageUsed in clinical research to prepare datasets for analysisUsed to interpret data, generate reports, and support decision-making

While both roles involve working with clinical data, Clinical Data Programmers focus on coding and preparing datasets, whereas Clinical Data Analysts interpret data and generate insights. Understanding these differences helps in choosing the right career path or job search focus.

What are popular job titles related to Clinical Data Programmer jobs in Chicago, IL?

For Clinical Data Programmer jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Clinical Data Programmer jobs in Chicago, IL look for?

The top searched job categories for Clinical Data Programmer jobs in Chicago, IL are:

Infographic showing various Clinical Data Programmer job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $122,548 per year, or $58.9 per hour.

Clinical Data Scientist

RedSail Technologies, LLC

Oak Brook, IL • On-site, Remote

$140K - $145K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


Job description

Clinical Data ScientistJob Summary

The RedSail Advantage Solutions has the primary mission to create incremental value streams for RedSail through the development and activation of Clinical, Financial, & Operational Programs that leverage our uniquely integrated technology platforms as well as our associated reach within the targeted market segments. The Clinical Data Scientist, will participate in the making use of RedSail’s data to evaluate and establish various impactful programs to accomplish and assist with the measurement of program effectiveness against the department objectives.

Key Duties
  • Data Collection: Gathering data from various sources, such as databases, APIs, web scraping, and more. This can involve collecting structured and unstructured data.
  • Data Cleaning: Preprocessing the collected data to handle missing values, remove duplicates, correct inconsistencies, and address outliers. This step ensures data quality and reliability.
  • Data Exploration (Exploratory Data Analysis, EDA): Analyzing the main characteristics of the data often through visualization and summary statistics. This helps in understanding data distributions, relationships between variables, and identifying patterns or anomalies.
  • Data Transformation: Modifying data into a suitable format for analysis, such as normalization, standardization, or creating new features (feature engineering).
  • Data Visualization: Creating visual representations of data, such as graphs, charts, and dashboards, to communicate findings effectively. Tools like Matplotlib, Seaborn, and Tableau are commonly used.
  • Statistical Analysis: Applying statistical methods to understand data distributions, test hypotheses, and infer relationships. This can include t-tests, chi-square tests, ANOVA, and regression analysis.
  • Data Communication: Presenting findings, insights, and recommendations to stakeholders through reports, presentations, and storytelling. Effective communication is crucial for decision-making.
  • Collaboration with Domain Experts: Working with professionals from various fields to ensure that the data science approach aligns with business goals and that the results are meaningful and actionable.
  • Keeping Up with Industry Trends: Continuously learning and adapting to new tools, technologies, and methodologies in data science to stay current and effective in the field.
  • Ethical Considerations and Compliance: Ensuring that data usage complies with ethical standards and legal regulations, such as data privacy laws (e.g., HIPAA)
Education/Training
  • Bachelor’s degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree. Doctor of Pharmacy with data credentials or extensive data experience may substitute for formal education in Data Science.
Required Work Skills/Experience
  • Pharma/Pharmacy/Healthcare experience.
  • Experience programming with SQL scripting.
  • Experience with data analytics visualization tools such as PowerBI and Tableau.
  • Ability to transform complex data across multiple platforms into concise datasets.
  • Ability to visualize data in the most effective way possible for a given project or study.
  • Strong analytical and problem-solving skills; inquisitive.
  • Ability to work independently and with team members from different backgrounds and collaborative styles.
  • Excellent attention to detail with critical thinking skills.
Preferred Work Skills/Experience
  • A combination of both Doctor of Pharmacy and degree in Data Science, Data Engineering, or similar data relevant computer science/software development degree (i.e. Pharmacist Data Scientist) strongly preferred.
  • 2 years of experience as a Data Analyst, Data Scientist or Data Engineer.
  • Experience with Pharma/Pharmacy transactions.
  • Experience programming with Python or Go Lang.
Discretionary Judgement
  • Uses independent judgment and discretion based upon the employee’s experience in the position and knowledge of the products, equipment, and services.
  • Uses good judgment and possesses ethical work values.
Physical Demands/Working Conditions/General Employment
  • Moderate or high stress levels may be experienced in the job performance.
  • Position is performed in a general office environment, home office, or approved remote workspace where physical work includes, but is not limited to, sitting, standing, reaching, kneeling, bending, and lifting to 25 lbs.
Equipment
  • Daily use of Microsoft Teams (phone), computer, printer, and other routine office equipment.
  • Must have reliable and consistent internet access.
Safety to Self and Others
  • Little responsibility for the safety of others. Job is performed in an office setting where there are no hazardous materials or equipment.
Working Conditions/Hazards
  • Position is performed in an open office environment or approved remote work location.
Compensation & Total Rewards
  • The anticipated base salary range for this position is $140,000-$145,000 annually. This position is also eligible for an annual target bonus of 4%. Actual compensation will be determined based on factors including relevant experience, skills, qualifications, and geographic location.
  • Benefits include paid time off, medical, dental, and vision insurance, a 401(k) with a 5% company match, a fitness bonus, professional development opportunities, and programs that support overall well-being.
Work Location
  • Hybrid at a RedSail Office
    • Spartanburg, SC
    • Irving, TX
    • Shreveport, LA
    • Oak Brook, IL
    • Cranberry Township, PA
    • Long Island, NY