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Clinical Data Associate Jobs in Reston, VA (NOW HIRING)

... Associate Director of Artificial Intelligence, Modeling, and Data to lead our charge at the ... saving clinical research. Sitting at the nexus of our Data Science and Biomedical Research ...

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... Associate Director of Artificial Intelligence, Modeling, and Data to lead our charge at the ... saving clinical research. Sitting at the nexus of our Data Science and Biomedical Research ...

Clinical Research Associate - Multi Therapeutic Area (Early Development) - West Region ICON is a ... Resolve data queries and drive timely, high-quality data entry * Document site progress and ...

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Clinical Data Associate information

See Reston, VA salary details

$14

$40

$90

How much do clinical data associate jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for clinical data associate in Reston, VA is $40.52, according to ZipRecruiter salary data. Most workers in this role earn between $30.53 and $40.53 per hour, depending on experience, location, and employer.

What are some common challenges faced by Clinical Data Associates when ensuring data quality during clinical trials?

Clinical Data Associates often encounter challenges such as identifying and resolving discrepancies in large datasets, maintaining strict compliance with regulatory standards, and coordinating timely data entry from multiple sites. They must work closely with clinical research teams and data managers to clarify ambiguous data and implement data cleaning procedures. Staying organized and detail-oriented is essential to ensure data accuracy and the successful progression of clinical trials.

Which is better, CDM or SAS?

For a Clinical Data Associate, SAS is a widely used software for data analysis and reporting in clinical trials, while CDM (Clinical Data Management) refers to the overall process and systems used to collect, clean, and manage clinical data. SAS skills are often essential for data analysis tasks, whereas CDM involves understanding data collection tools, databases, and validation processes. Both are important in the clinical research environment, and proficiency in SAS can enhance a data associate's ability to perform analyses efficiently.

What's next after CRC?

After working as a Clinical Research Coordinator (CRC), professionals often advance to roles such as Clinical Data Associate, Clinical Trial Manager, or Regulatory Affairs Specialist. Gaining experience, certifications like CCRP, and developing skills in data management and regulatory compliance can facilitate career progression in clinical research.

What are the key skills and qualifications needed to thrive as a Clinical Data Associate, and why are they important?

To thrive as a Clinical Data Associate, you need a solid understanding of clinical research, data management principles, and attention to detail, often supported by a degree in life sciences or a related field. Familiarity with clinical data management systems (CDMS), electronic data capture (EDC) tools, and knowledge of regulatory guidelines like GCP or CDISC is typically required. Strong organizational skills, analytical thinking, and clear communication set outstanding candidates apart in this role. These skills ensure the accuracy, integrity, and compliance of clinical trial data, which are crucial for successful research outcomes and regulatory approval.

What does a Clinical Data Associate do?

A Clinical Data Associate is responsible for collecting, validating, and managing clinical trial data to ensure its accuracy, completeness, and compliance with regulatory standards. They work closely with clinical research teams to monitor data quality, resolve discrepancies, and prepare data for analysis. Their work is essential in supporting drug development and regulatory submissions by ensuring reliable and high-quality clinical data.

What is the role of a clinical data associate?

A clinical data associate is responsible for collecting, managing, and ensuring the accuracy of data from clinical trials. They review data for completeness, resolve discrepancies, and use database tools to support data integrity and regulatory compliance throughout the trial process.

What Does a Clinical Data Associate Do?

A clinical data associate is responsible for tracking data and results in a research study. As a clinical data associate, your job duties are to collect data, perform data management, and input data into any software used by your team. You work on a research team, so you must be able to work collaboratively and have excellent organizational skills. While you spend most of your time in an office, you may be required to work in the field to record data. The only universal qualifications needed for this career are a background in health care or medical science research and experience with data management software like Oracle Clinical, Microsoft Excel, and SPSS.

Do you need a degree to be a CRC?

A Clinical Data Associate (CDA) typically does not require a specific degree, but a background in life sciences, healthcare, or related fields is often preferred. Many employers value relevant certifications and experience with clinical data management tools. Educational requirements can vary by employer and job level.

Is CRA an entry level job?

A Clinical Data Associate (CDA) role is typically considered an entry-level position in clinical research, often requiring a bachelor's degree in a related field and some familiarity with data management tools. However, a Clinical Research Associate (CRA) role usually requires more experience and is considered a mid- to senior-level position, involving site monitoring and regulatory compliance. Entry-level roles may serve as a stepping stone toward CRA positions with additional experience and certifications.

What is the difference between Clinical Data Associate vs Clinical Research Coordinator?

AspectClinical Data AssociateClinical Research Coordinator
Primary RoleManage and ensure accuracy of clinical trial dataOversee trial operations, patient recruitment, and site management
CredentialsBachelor's in life sciences or related field; familiarity with data managementBachelor's in health sciences or related field; clinical trial experience
Work EnvironmentData management teams, clinical trial databasesClinical sites, hospitals, research facilities
Industry UsagePharmaceutical companies, CROs, biotech firmsHospitals, research institutions, clinical trial sites

While both roles support clinical trials, a Clinical Data Associate primarily focuses on managing and validating trial data, ensuring accuracy and compliance. In contrast, a Clinical Research Coordinator handles the overall trial operations, including patient recruitment and site coordination. Both roles require relevant certifications and work within the clinical research industry, but their daily responsibilities differ significantly.

What are the most commonly searched types of Clinical Data jobs in Reston, VA? The most popular types of Clinical Data jobs in Reston, VA are:
What are popular job titles related to Clinical Data Associate jobs in Reston, VA? For Clinical Data Associate jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Clinical Data Associate jobs in Reston, VA look for? The top searched job categories for Clinical Data Associate jobs in Reston, VA are:
What cities near Reston, VA are hiring for Clinical Data Associate jobs? Cities near Reston, VA with the most Clinical Data Associate job openings:
Infographic showing various Clinical Data Associate job openings in Reston, VA as of June 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $84,290 per year, or $40.5 per hour.
Associate Director of AI and Data

Associate Director of AI and Data

Axle

Rockville, MD • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 15 days ago

Be an early applicant


Job description

(ID: 2026-1573)


Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).

Benefits We Offer:

  • 100% Medical, Dental & Vision Coverage for Employees
  • Paid Time Off and Paid Holidays
  • 401K match up to 5%
  • Educational Benefits for Career Growth
  • Employee Referral Bonus
  • Flexible Spending Accounts:
    • Healthcare (FSA)
    • Parking Reimbursement Account (PRK)
    • Dependent Care Assistant Program (DCAP)
    • Transportation Reimbursement Account (TRN)

Axle is seeking a visionary and operationally astute Associate Director of Artificial Intelligence, Modeling, and Data to lead our charge at the frontier of biomedical innovation. In this pivotal leadership role, you will architect the future of AI-driven discovery, bridging the gap between advanced computational science and life-saving clinical research.

Sitting at the nexus of our Data Science and Biomedical Research divisions, you will oversee the strategic development and deployment of high-performance AI/ML solutions that empower federal health agencies, including the National Institutes of Health (NIH) and the National Center for Advancing Translational Sciences (NCATS). You will be the technical conscience and strategic driver for a diverse portfolio of projects, ranging from the optimization of our open-source Polus platform to the implementation of Generative AI pipelines for drug discovery and high-dimensional data analysis.

This is not merely a management role; it is a mission-critical position for a leader who is passionate about the "public good" of science. You will galvanize interdisciplinary teams of PhD scientists, machine learning engineers, and software architects to solve complex health challenges, such as pandemic preparedness and rare disease treatment. As an Associate Director, you will combine deep technical expertise with executive presence, serving as a trusted advisor to government stakeholders and a key architect of Axle's long-term growth in the federal health IT sector.

Core Responsibilities:1. Strategic Leadership of the AI/ML Roadmap
  • Visionary Architecture: Architect and execute a comprehensive AI/ML strategy that aligns Axle's technical capabilities with the NIH Strategic Plan for Data Science (2025–2030). You will define the long-term vision for integrating Generative AI, Large Language Models (LLMs), and Agentic Workflows into federal research environments, moving beyond static analysis to active, AI-assisted discovery.

  • Platform Evolution (Polus): Spearhead the evolution of the Polus platform, transitioning it from a robust image analysis tool into a fully integrated, multi-modal research ecosystem. You will oversee the roadmap for new feature development, ensuring scalability, security, and interoperability across cloud environments (AWS/GCP/Azure) using containerized architectures (Docker/Kubernetes).

  • AI Governance & Compliance: Establish and enforce rigorous AI Governance frameworks. You will operationalize the NIST AI Risk Management Framework (RMF) across all projects to ensure fairness, interpretability, and compliance with federal ethical standards. You will lead "Gap Analysis" and "Risk Management" exercises to ensure all AI deployments are trustworthy and transparent.

2. Oversight of Complex Modeling & High-Dimensional Data Pipelines
  • Petabyte-Scale Engineering: Direct the design and implementation of high-throughput data pipelines capable of ingesting and analyzing petabyte-scale datasets (genomics, proteomics, EHR). You will ensure these systems adhere to FAIR data principles (Findable, Accessible, Interoperable, Reusable), facilitating seamless data sharing across NIH institutes and global research centers.

  • Translational Science De-risking: Oversee the development of predictive models for translational science, focusing on "de-risking" drug discovery and clinical trial design. This involves guiding technical teams in the application of deep learning techniques to identify molecular targets, predict therapeutic outcomes, and simulate clinical scenarios (Digital Twins).

  • Operational Excellence (MLOps): Optimize MLOps and DevSecOps processes to ensure the rapid, secure deployment of models from prototype to production. You will champion a culture of "automation first," reducing time-to-insight for researchers by streamlining the transition from Jupyter notebooks to containerized, cloud-native services.

3. Business Development & Federal Growth (Capture Support)
  • Lead Solution Architect: Partner with the Growth and Capture teams to drive new business acquisition. You will serve as the Lead Solution Architect for major proposal efforts ($50M+), authoring technical volumes, developing win themes, and creating compelling solution graphics that demonstrate Axle's technical differentiation.

  • Proposal Authorship: Personally write key sections of technical proposals, including the "Technical Approach," "Staffing Plan," and "Risk Mitigation" volumes. You will translate complex agency requirements into winning narratives that score highly with federal evaluators.

  • Client Liaison: Galvanize relationships with key federal stakeholders (Project Officers, CIOs, Lab Chiefs). You will act as the primary technical liaison, translating complex agency requirements into deliverable technical solutions and presenting these visions in competitive "Black Hat" sessions and oral presentations.

4. Mentorship of Data Scientists & Engineers
  • Interdisciplinary Team Building: Cultivate a high-performance, interdisciplinary team culture. You will manage and mentor a diverse group of data scientists, bioinformaticians, and software engineers, fostering an environment of psychological safety where "expert" scientific knowledge seamlessly integrates with "agile" engineering practices.

  • Continuous Learning: Drive continuous learning and upskilling initiatives. You will establish internal "Communities of Practice" for AI and Data Science, ensuring that Axle's workforce remains at the bleeding edge of technologies like Graph Neural Networks and Federated Learning.

  • Democratization of AI: Democratize access to AI tools within the client environment. You will lead efforts to create "low-code/no-code" interfaces and training programs that empower non-technical NIH researchers to utilize advanced analytics independently.

Required Qualifications: To effectively lead in this high-stakes environment, candidates must possess a rare combination of advanced academic training and battle-tested industry experience.

Education:

  • Ph.D. in Computer Science, Bioinformatics, Computational Biology, Data Science, or a related quantitative discipline is highly preferred to ensure peer-level credibility with NIH scientists.

  • Alternatively, a Master's degree in one of the above fields with exceptional, demonstrated leadership experience in a federal or research-intensive setting will be considered.

Experience:

  • 8–10+ years of progressive experience in data science, AI/ML engineering, or computational biology, with a focus on high-dimensional data.

  • 3–5+ years of leadership experience managing cross-functional teams (e.g., managing both PhD researchers and software developers) in a matrixed organization.

  • Federal Contracting Experience: Demonstrated experience with Federal Business Development, including writing technical proposals and supporting capture activities for contracts valued at $15M+.

  • Regulatory Experience: Proven track record of delivering complex AI/ML solutions in a regulated environment, with specific familiarity with HIPAA, FedRAMP, or NIST AI RMF compliance.

Technical Skills: The Assistant Director must possess deep, hands-on technical fluency to command respect from engineering teams and validate architectural decisions.
  • Core AI/ML: Expert-level understanding of Deep Learning frameworks (PyTorch, TensorFlow), Classical Machine Learning (Scikit-Learn), and Generative AI architectures (Transformers, LLMs, RAG).

  • Languages: Proficiency in Python (primary) and R (secondary); familiarity with Java or C++ (for Polus backend optimization) is a strong plus.

  • Cloud Architecture: Extensive experience with Cloud-Native AI pipelines on AWS (SageMaker, HealthLake), GCP (Vertex AI, BigQuery), or Azure. Knowledge of the NIH STRIDES initiative and cloud economics is essential.

  • Data Engineering: Mastery of big data technologies (Spark, Databricks) and workflow orchestration tools (Airflow, Nextflow, Cromwell).

  • MLOps & DevOps: Strong knowledge of containerization (Docker, Kubernetes), CI/CD pipelines (GitHub Actions, Jenkins), and model monitoring/governance tools.

  • Visualization & Platforms: Experience with advanced visualization tools (DeepZoom, WebGL) and platform development (building APIs, microservices).

Preferred Skills: Candidates with the following specific experiences will be given immediate priority:
  • NIH Ecosystem Experience: Direct experience working with NIH, NCATS, NIAID, or similar federal health agencies. Understanding of the specific data challenges within the federal health sector is highly valued.

  • Open Source Leadership: Contributions to or leadership of open-source scientific software projects. Specific familiarity with the Polus platform or the National COVID Cohort Collaborative (N3C) data enclave is a distinct advantage.

  • NIST AI RMF Practitioner: Demonstrated experience implementing the NIST AI Risk Management Framework (Map, Measure, Manage, Govern) in a real-world setting.

  • Domain Expertise: Specialized knowledge in High-Content Imaging, Cheminformatics, Genomics, or Real-World Data (RWD) analytics.

Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.

The diversity of Axle's employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.

Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location.

#IND

Salary Range
$150,000—$190,000 USD