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Informatics Jobs in Massachusetts (NOW HIRING)

Software Engineer, UI

Boston, MA

$113K - $151K/yr

... Watershed Informatics is hiring an experienced UI Software Engineer to design and build powerful interface features for our genomic analysis and system management software. We're looking for ...

Showing results 41-60

Informatics information

See Massachusetts salary details

$46.4K

$107.5K

$181.8K

How much do informatics jobs pay per year?

As of Aug 8, 2026, the average yearly pay for informatics in Massachusetts is $107,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,400.00 and $133,800.00 per year, depending on experience, location, and employer.

How does an informatics professional typically collaborate with other departments in a healthcare setting?

Informatics professionals in healthcare frequently work alongside clinicians, IT staff, and administrative teams to implement and optimize electronic health record systems, improve data workflows, and ensure compliance with regulations. They often serve as a bridge between technical teams and end users, translating technical requirements into practical solutions that enhance patient care and operational efficiency. Regular cross-functional meetings and project-based collaborations are common, making strong communication and teamwork skills essential for success in this role.

What are the key skills and qualifications needed to thrive as an informatics specialist?

To thrive as an Informatics Specialist, you need expertise in data analysis, information systems, and domain-specific knowledge, often supported by a degree in informatics, computer science, or a related field. Familiarity with tools like SQL, Python, EHR systems, and relevant certifications such as Certified Health Informatics Systems Professional (CHISP) are commonly required. Strong problem-solving, analytical thinking, and effective communication skills help bridge gaps between technical teams and stakeholders. These abilities are crucial for transforming data into actionable insights and optimizing technology solutions in various industries.

What is the difference between Informatics vs Medical Coding?

AspectInformaticsMedical Coding
Required CredentialsDegree in health informatics, certifications like RHIA or RHITCertification as Certified Professional Coder (CPC) or CCS
Work EnvironmentHospitals, clinics, health IT companies, researchHospitals, physician offices, billing companies
Industry UsageHealth IT, data management, clinical systemsMedical billing, claims processing, coding audits

Informatics focuses on managing health data and improving healthcare systems, requiring a background in health IT and data analysis. Medical coding involves translating medical procedures and diagnoses into standardized codes for billing and insurance purposes. While both roles are essential in healthcare, informatics professionals work on system implementation and data management, whereas medical coders focus on accurate coding for reimbursement.

What are the most commonly searched types of Informatics jobs in Massachusetts? The most popular types of Informatics jobs in Massachusetts are:
What cities in Massachusetts are hiring for Informatics jobs? Cities in Massachusetts with the most Informatics job openings:
Infographic showing various Informatics job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 11% Part Time, and 6% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $107,474 per year, or $51.7 per hour.

Postdoctoral Fellow in Biomedical Informatics (Cai Lab)

Harvard University

Cambridge, MA • On-site

$54K - $73K/yr

Full-time

Re-posted 19 days ago


Harvard University rating

8.5

Company rating: 8.5 out of 10

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Job description

Position
Details
Title
Postdoctoral Fellow in Biomedical Informatics (Cai Lab)
School
Harvard Medical School
Department/Area
Biomedical Informatics
Position Description
A Postdoctoral Research Fellow position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic research group focused on several synergistic goals: generating actionable Real-World Evidence (RWE) from multi-institutional Electronic Health Records (EHR), improving the generalizability of clinical evidence across diverse populations using multi-source and multi-modal data, and accelerating drug discovery by leveraging these rich, integrated datasets. This role offers a unique opportunity to develop methodological innovations that bridge the gap between computational theory and impactful clinical application.
We are seeking a highly motivated individual with a strong statistical and machine learning background. The ideal candidate will have existing expertise in several of the following areas, aligned with our research focus: 1) Causal inference, invariant learning and representation learning; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing.
Basic Qualifications
Candidates must hold a Ph.D. in a quantitative field, such as statistics, biostatistics, computer science, or a related discipline. Success in this position requires strong quantitative research capabilities and demonstrated proficiency in programming, specifically in Python and R, as well as experience with modern deep learning frameworks like PyTorch or TensorFlow. In addition to technical skills, the candidate must possess excellent written and oral communication abilities to effectively disseminate research findings and collaborate within a multidisciplinary team.
Additional Qualifications
Special Instructions
Contact Information
Mo Moro
Contact Email
mohammed_moro@hms.harvard.edu
Salary Range
Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, can be found at https://postdoc.hms.harvard.edu/guidelines
Minimum Number of References Required
Maximum Number of References Allowed
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