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Clinical R Programmer Jobs in Carrollton, TX (NOW HIRING)

CYNET SYSTEMS

Cerner Delivery Manager

Dallas, TX · On-site

$65/hr

... Clinical modules (FirstNet, CareAware, Nursing), Ancillaries (PathNet, RadNet, Pharmacy), and Core ... programming languages like Python/R. * Ensure security, access, and compliance awareness.

micro1 AI

Digital Chemistry Specialist - Remote

Plano, TX · Remote

$90 - $120/hr

Evaluate and synthesize findings from biological, chemical, and clinical data sources. * Offer ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

micro1 AI

Digital Chemistry Specialist - Remote

Allen, TX · Remote

$90 - $120/hr

Evaluate and synthesize findings from biological, chemical, and clinical data sources. * Offer ... programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). * Strong ...

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All JobsClinical R Programmer JobsClinical R Programmer Jobs in Carrollton, TX

Clinical R Programmer information

See Carrollton, TX salary details

$23

$62

$99

How much do clinical r programmer jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for clinical r programmer in Carrollton, TX is $62.52, according to ZipRecruiter salary data. Most workers in this role earn between $51.73 and $70.77 per hour, depending on experience, location, and employer.

What skills and qualifications are needed to be a Clinical R programmer?

To thrive as a Clinical R Programmer, you need a solid background in statistics, R programming, and clinical trial data analysis, often supported by a degree in statistics, biostatistics, or a related field. Expertise in SAS, CDISC standards (SDTM/ADaM), and familiarity with clinical data management systems are commonly required. Attention to detail, problem-solving skills, and effective communication enable you to interpret data accurately and collaborate with cross-functional teams. These skills are vital for ensuring reliable statistical outputs that support regulatory submissions and data-driven decisions in clinical research.

What is a Clinical R programmer?

Clinical R Programmers are professionals who use the R programming language to manage, analyze, and visualize clinical trial data in the pharmaceutical, biotech, or healthcare industries. They play a key role in preparing statistical reports, generating tables, listings, and figures (TLFs), and ensuring data integrity for regulatory submissions. Clinical R Programmers collaborate with statisticians, data managers, and clinical teams to ensure the accuracy and compliance of clinical trial results with industry standards and regulatory requirements.

What are common challenges faced by Clinical R programmers when working with clinical trial data?

Clinical R Programmers often encounter challenges such as handling large and complex datasets, ensuring strict compliance with regulatory standards (like CDISC SDTM and ADaM), and maintaining data integrity throughout the analysis process. Collaboration can be demanding, as programmers must frequently coordinate with biostatisticians, data managers, and clinical teams to interpret data requirements and resolve discrepancies. Staying updated with evolving industry guidelines and managing tight project timelines are also common aspects of the role.

What is the difference between Clinical R Programmer vs Clinical SAS Programmer?

AspectClinical R ProgrammerClinical SAS Programmer
Required CredentialsTypically requires a degree in statistics, biostatistics, or related field; proficiency in R programmingUsually requires a degree in statistics, biostatistics, or related field; proficiency in SAS programming
Work EnvironmentOften works in research-focused settings, academia, or biotech companies using open-source toolsCommonly employed in pharmaceutical companies, CROs, and clinical trial data analysis using SAS
Industry UsageGrowing in popularity for data analysis and visualization in clinical researchStandard in clinical trial data management and regulatory submissions

While both roles involve programming for clinical data analysis, Clinical R Programmers focus on using R for statistical analysis and visualization, whereas Clinical SAS Programmers primarily use SAS for data management and reporting. The choice depends on the company's preferred tools and project requirements.

What are popular job titles related to Clinical R Programmer jobs in Carrollton, TX? For Clinical R Programmer jobs in Carrollton, TX, the most frequently searched job titles are:
What cities near Carrollton, TX are hiring for Clinical R Programmer jobs? Cities near Carrollton, TX with the most Clinical R Programmer job openings:
Clinical R Programmer jobs near you

AI Training Specialist - Life Sciences

micro1 AI

Garland, TX • Remote

$90 - $120/hr

Part-time

Posted 10 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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