Clinical Data Analyst Jobs in Maryland
Clinical Data Analyst jobs in Maryland are concentrated in the healthcare, biopharmaceutical, and federal health research sectors, with demand at every level from entry-level to senior principal. Most hiring is centered in Baltimore, Bethesda, and the Rockville-Gaithersburg corridor, where organizations like Johns Hopkins Health System, the National Institutes of Health, and CareFirst BlueCross BlueShield maintain a steady presence. The most in-demand specialties are oncology trial data management, real-world evidence analysis, and EDC platform administration. See the openings below and apply to the ones that match your experience.
Find Clinical Data Analyst JobsOverview
Showing 5 of 8+ Clinical Data Analyst jobs
The Johns Hopkins Data Science and AI Institute (DSAI) is a pan-institutional initiative at Johns Hopkins to advance artificial intelligence and its applications, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance.
DSAI seeks a Research Software Engineer – Image Analysis & Microscopy with strong academic and industry background focused on designing and building software for state-of-the-art AI and data science applications across diverse scientific domains. The successful candidates will work at the cutting edge of modern science in collaboration with DSAI affiliated faculty at Johns Hopkins University (JHU) on projects ranging from consulting and short-term service engagements to large, multiyear AI and data science initiatives and applications. DSAI will address the growing demand for high-quality professional software engineers within academia who can build dynamic, scalable, open software to facilitate accelerated scientific discovery across disciplines.
The DSAI engineers will be at the forefront of modern data intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability.
Specific Duties & Responsibilities
- Work collaboratively in a team with other RSEs and scientists.
- Participates in ground-breaking research projects that need advanced software solutions requiring expertise in software engineering not commonly found in scientific collaborations.
The projects may,
- Require the creation of AI/ML solutions using the latest deep learning libraries trained on state-of-the-art hardware.
- Involve analysis of massive data sets either in the cloud or on premises.
- Require creation of novel data science techniques, software pipelines for processing of real-time high-frequency data processing workflows and may need the design of complex database models for storing and disseminating scientific data sets.
- Require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement.
- Require software solutions developed from scratch or refactoring existing solutions to make them conform to industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.).
- It is a high-level goal of DSAI to translate the efforts for individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects.
- Develop software to implement novel scientific research algorithms.
- Create and run data processing workflows utilizing on-premises or cloud-based. computing infrastructure.
- Develop data models.
- Co-author scientific publications describing software and/or other contributions.
- Translate recurring themes from specific projects into frameworks and template patterns. for sustainable scientific infrastructure benefiting future projects.
Lead and participate in service activities, potentially including
- Providing guidance to faculty, staff, and students on AI, data science and software engineering.
- Developing and delivering presentations and short courses.
- Attending conferences and workshops.
- Code quality reviews.
- Hiring.
- Other activities as needed.
Special Knowledge, Skills, and Abilities required
- Expert-level knowledge of Python and/or C++ and willingness to learn other languages as needed.
- Expert-level knowledge of multiple modern AI/ML, vision, NLP, bioinformatics and/or mathematical or computational libraries.
- Familiarity with software containerization technologies such as Docker and Singularity.
- Familiarity with RESTful web service principles and development.
- Familiarity with SQL and relational database principles and development.
- Fluency in the Linux operating system and related tools.
- Familiarity with modern software engineering best practices, such as Git source control, peer code review, test-driven development, build automation and continuous integration / continuous delivery.
- Familiarity with cloud development and deployment.
- Demonstrated leadership and self-direction.
- Willingness to teach others both informally and in short course format.
- Willingness to continually learn new tools and techniques as needed.
- Excellent verbal and written communication.
Minimum Qualifications
- Masters in a Quantitative Discipline such as Computer Science, Engineering, Physics or Bioinformatics with strong scientific computing and/or mathematics background.
- Three (3) years’ experience working in software development in large projects and three (3) years’ experience in development and application of
- AI/ML: developing, training and applying state of the art models in practical scientific applications aligned with DSAI domains, or
- Data science: modeling, transforming, applying ETL pipelines, and similar operations to complex data sets at scale.
- Additional education may substitute for required experience, and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula.
Preferred Qualifications
- PhD in a quantitative discipline (highly preferred).
- Five (5) years’ experience as above in either AI/ML or data science concentration.
- Experience with one or more of,
- Image analysis
- Microscopy
- Particle tracking
- Data management for high-throughput screening
- Experience developing, training, fine-tuning and applying LLMs and/or foundational models.
- Experience deploying AI models onto clinical platforms.
- Familiarity with data formats common in scientific domains such as medical imaging, genomic sequences, proteins, chemical structures, geospatial, oceanographic, and heath record data.
- Experience in CUDA GPU programming.
- Experience authoring open-source Python packages in PyPI.
- Experience in open-source project governance.
- Experience in open-source community adoption initiatives.
Classified Title: Scientific Software Engineer
Job Posting Title (Working Title): Research Software Engineer – Image Analysis & Microscopy (Data Science and AI Institute)
Role/Level/Range: APPTSTAF/01/ST
Starting Salary Range: Commensurate w/exp.
Employee group: Full Time
Schedule: M-F, 37.5 hrs wkly
FLSA Status: Exempt
Location: Hybrid/Mount Washington Campus
Department name: DSAI Institute
Personnel area: Whiting School of Engineering
Total Rewards
The referenced base salary range represents the low and high end of Johns Hopkins University’s salary range for this position. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, market conditions, education/training and other qualifications. Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.
Education and Experience Equivalency
Please refer to the job description above to see which forms of equivalency are permitted for this position. If permitted, equivalencies will follow these guidelines: JHU Equivalency Formula: 30 undergraduate degree credits (semester hours) or 18 graduate degree credits may substitute for one year of experience. Additional related experience may substitute for required education on the same basis. For jobs where equivalency is permitted, up to two years of non-related college course work may be applied towards the total minimum education/experience required for the respective job.
Applicants Completing Studies
Applicants who do not meet the posted requirements but are completing their final academic semester/quarter will be considered eligible for employment and may be asked to provide additional information confirming their academic completion date.
Background Checks
The successful candidate(s) for this position will be subject to a pre-employment background check. Johns Hopkins is committed to hiring individuals with a justice-involved background, consistent with applicable policies and current practice. A prior criminal history does not automatically preclude candidates from employment at Johns Hopkins University. In accordance with applicable law, the university will review, on an individual basis, the date of a candidate's conviction, the nature of the conviction and how the conviction relates to an essential job-related qualification or function.
Diversity and Inclusion
The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
EEO is the Law
https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf
Accommodation Information
If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the Talent Acquisition Office at jhurecruitment@jhu.edu. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations or accessibility at Johns Hopkins University, please visit: https://accessibility.jhu.edu/.
Vaccine Requirements
Johns Hopkins University requires all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry.
The following additional provisions may apply, depending upon campus. Your recruiter will advise accordingly.
The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.
The Johns Hopkins Data Science and AI Institute (DSAI) is a pan-institutional initiative at Johns Hopkins to advance artificial intelligence and its applications, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance.
DSAI seeks a Research Software Engineer – Image Analysis & Microscopy with strong academic and industry background focused on designing and building software for state-of-the-art AI and data science applications across diverse scientific domains. The successful candidates will work at the cutting edge of modern science in collaboration with DSAI affiliated faculty at Johns Hopkins University (JHU) on projects ranging from consulting and short-term service engagements to large, multiyear AI and data science initiatives and applications. DSAI will address the growing demand for high-quality professional software engineers within academia who can build dynamic, scalable, open software to facilitate accelerated scientific discovery across disciplines.
The DSAI engineers will be at the forefront of modern data intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability.
Specific Duties & Responsibilities
- Work collaboratively in a team with other RSEs and scientists.
- Participates in ground-breaking research projects that need advanced software solutions requiring expertise in software engineering not commonly found in scientific collaborations.
The projects may,
- Require the creation of AI/ML solutions using the latest deep learning libraries trained on state-of-the-art hardware.
- Involve analysis of massive data sets either in the cloud or on premises.
- Require creation of novel data science techniques, software pipelines for processing of real-time high-frequency data processing workflows and may need the design of complex database models for storing and disseminating scientific data sets.
- Require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement.
- Require software solutions developed from scratch or refactoring existing solutions to make them conform to industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.).
- It is a high-level goal of DSAI to translate the efforts for individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects.
- Develop software to implement novel scientific research algorithms.
- Create and run data processing workflows utilizing on-premises or cloud-based. computing infrastructure.
- Develop data models.
- Co-author scientific publications describing software and/or other contributions.
- Translate recurring themes from specific projects into frameworks and template patterns. for sustainable scientific infrastructure benefiting future projects.
Lead and participate in service activities, potentially including
- Providing guidance to faculty, staff, and students on AI, data science and software engineering.
- Developing and delivering presentations and short courses.
- Attending conferences and workshops.
- Code quality reviews.
- Hiring.
- Other activities as needed.
Special Knowledge, Skills, and Abilities required
- Expert-level knowledge of Python and/or C++ and willingness to learn other languages as needed.
- Expert-level knowledge of multiple modern AI/ML, vision, NLP, bioinformatics and/or mathematical or computational libraries.
- Familiarity with software containerization technologies such as Docker and Singularity.
- Familiarity with RESTful web service principles and development.
- Familiarity with SQL and relational database principles and development.
- Fluency in the Linux operating system and related tools.
- Familiarity with modern software engineering best practices, such as Git source control, peer code review, test-driven development, build automation and continuous integration / continuous delivery.
- Familiarity with cloud development and deployment.
- Demonstrated leadership and self-direction.
- Willingness to teach others both informally and in short course format.
- Willingness to continually learn new tools and techniques as needed.
- Excellent verbal and written communication.
Minimum Qualifications
- Masters in a Quantitative Discipline such as Computer Science, Engineering, Physics or Bioinformatics with strong scientific computing and/or mathematics background.
- Three (3) years’ experience working in software development in large projects and three (3) years’ experience in development and application of
- AI/ML: developing, training and applying state of the art models in practical scientific applications aligned with DSAI domains, or
- Data science: modeling, transforming, applying ETL pipelines, and similar operations to complex data sets at scale.
- Additional education may substitute for required experience, and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula.
Preferred Qualifications
- PhD in a quantitative discipline (highly preferred).
- Five (5) years’ experience as above in either AI/ML or data science concentration.
- Experience with one or more of,
- Image analysis
- Microscopy
- Particle tracking
- Data management for high-throughput screening
- Experience developing, training, fine-tuning and applying LLMs and/or foundational models.
- Experience deploying AI models onto clinical platforms.
- Familiarity with data formats common in scientific domains such as medical imaging, genomic sequences, proteins, chemical structures, geospatial, oceanographic, and heath record data.
- Experience in CUDA GPU programming.
- Experience authoring open-source Python packages in PyPI.
- Experience in open-source project governance.
- Experience in open-source community adoption initiatives.
Classified Title: Scientific Software Engineer
Job Posting Title (Working Title): Research Software Engineer – Image Analysis & Microscopy (Data Science and AI Institute)
Role/Level/Range: APPTSTAF/01/ST
Starting Salary Range: Commensurate w/exp.
Employee group: Full Time
Schedule: M-F, 37.5 hrs wkly
FLSA Status: Exempt
Location: Hybrid/Mount Washington Campus
Department name: DSAI Institute
Personnel area: Whiting School of Engineering
Total Rewards
The referenced base salary range represents the low and high end of Johns Hopkins University’s salary range for this position. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, market conditions, education/training and other qualifications. Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.
Education and Experience Equivalency
Please refer to the job description above to see which forms of equivalency are permitted for this position. If permitted, equivalencies will follow these guidelines: JHU Equivalency Formula: 30 undergraduate degree credits (semester hours) or 18 graduate degree credits may substitute for one year of experience. Additional related experience may substitute for required education on the same basis. For jobs where equivalency is permitted, up to two years of non-related college course work may be applied towards the total minimum education/experience required for the respective job.
Applicants Completing Studies
Applicants who do not meet the posted requirements but are completing their final academic semester/quarter will be considered eligible for employment and may be asked to provide additional information confirming their academic completion date.
Background Checks
The successful candidate(s) for this position will be subject to a pre-employment background check. Johns Hopkins is committed to hiring individuals with a justice-involved background, consistent with applicable policies and current practice. A prior criminal history does not automatically preclude candidates from employment at Johns Hopkins University. In accordance with applicable law, the university will review, on an individual basis, the date of a candidate's conviction, the nature of the conviction and how the conviction relates to an essential job-related qualification or function.
Diversity and Inclusion
The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
EEO is the Law
https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf
Accommodation Information
If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the Talent Acquisition Office at jhurecruitment@jhu.edu. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations or accessibility at Johns Hopkins University, please visit: https://accessibility.jhu.edu/.
Vaccine Requirements
Johns Hopkins University requires all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry.
The following additional provisions may apply, depending upon campus. Your recruiter will advise accordingly.
The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.
See All 8 Clinical Data Analyst Jobs in Maryland
Find roles in Maryland that match your experience and apply in just a few clicks.
Find Clinical Data Analyst JobsClinical Data Analyst Jobs by City in Maryland
Where Maryland roles are concentrated, by current openings.
Clinical Data Analyst Job Market in Maryland
A snapshot from current Maryland openings, updated as new roles post.
Who's Hiring
What Maryland Employers Look For
The qualifications that appear most often in clinical data analyst jobs across Maryland.
- Bachelor's degree in life sciences, public health, statistics, or a related field
- Hands-on experience with clinical data management systems such as Medidata Rave or Oracle Clinical
- Familiarity with CDISC standards including CDASH and SDTM for clinical trial data
- Proficiency in SAS, R, or SQL for data querying, cleaning, and analysis
- Knowledge of FDA 21 CFR Part 11 compliance and ICH E6 Good Clinical Practice guidelines
- Experience supporting Phase I through Phase III clinical trials or post-market studies
Clinical Data Analyst Jobs in Maryland: Frequently Asked Questions
How do you become a clinical data analyst in Maryland?
Most Maryland employers require a bachelor's degree in life sciences, statistics, bioinformatics, or public health as the starting point. Clinical data analyst roles in Maryland carry no state-issued license, but the Certified Clinical Data Manager credential offered by the Society for Clinical Data Management is widely recognized by Maryland employers, particularly those supporting NIH-sponsored or FDA-regulated trials. Building hands-on experience with CDISC standards and an EDC platform significantly strengthens your candidacy in this market.
How much do clinical data analysts make in Maryland?
Clinical data analysts in Maryland earn a median of about $136,370 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $77,930 for the lowest 10% to over $213,270 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire clinical data analysts in Maryland?
Companies currently hiring clinical data analysts in Maryland include Saalex, computercraft, and Cherokee Federal, per current listings on Migrate Mate as of September 2026. Maryland's concentration of biopharmaceutical contract research organizations and federal health agencies around the Baltimore-Washington corridor keeps demand for clinical data analysts consistently active throughout the year.
Which Maryland cities have the most clinical data analyst jobs?
The cities with the most clinical data analyst openings in Maryland are Bethesda, Lexington Park, and Baltimore. Baltimore drives volume through its dense network of academic medical centers and hospital systems, while Bethesda and Rockville reflect the NIH campus and the pharmaceutical and CRO corridor along Interstate 270 that has made Montgomery County one of the busiest life sciences hiring zones on the East Coast.
Are there remote clinical data analyst jobs in Maryland?
Yes, and more than most fields. About 100% of clinical data analyst openings tied to Maryland are remote or hybrid as of September 2026, reflecting how much of the work involves database management, data review, and report generation rather than on-site patient contact. Data cleaning, query resolution, and CDISC mapping work are the functions most commonly performed fully remote.
How can I get hired as a clinical data analyst in Maryland with little or no experience?
The most realistic entry path is through a clinical research coordinator or data entry associate role at a Maryland academic medical center or CRO, where you gain direct exposure to EDC systems and trial protocols. Johns Hopkins, University of Maryland Medical System, and the many Rockville and Gaithersburg CROs regularly post associate-level data management openings that do not require prior CDA experience. Completing a CDISC Interchange training course or earning an entry-level clinical research certificate from a Maryland community college or online program gives a measurable credential edge when competing for those positions.
Where can I find and apply to clinical data analyst jobs in Maryland?
You can find and apply to clinical data analyst jobs in Maryland on Migrate Mate, which lists current Maryland openings. Search the roles that fit your experience level and specialization, then apply directly to the ones that match your background.
See All 8 Clinical Data Analyst Jobs in Maryland
Find roles in Maryland that match your experience and apply in just a few clicks.
Find Clinical Data Analyst Jobs