Senior Medical Research Scientist (Remote)
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Key skills for this role
About the Role
Hire Feed seeks a Senior Medical Research Scientist for a remote contract role focused on advancing medical research through computational expertise.
Key Skills for This Role
Responsibilities
- Design and implement technical frameworks to process, analyze, and interpret complex medical datasets including imaging, genomic, or electronic health records
- Develop and validate machine learning models or statistical methods for predictive diagnostics, treatment optimization, or drug discovery applications
- Collaborate with cross functional research teams to integrate computational solutions into clinical workflows and validate performance in real world settings
- Ensure technical solutions comply with regulatory standards, data privacy requirements, and ethical guidelines in medical research
- Document methodologies, results, and system architectures to support reproducibility, peer review, and regulatory submissions
Requirements
- Master’s degree or higher in Computer Science, Biomedical Engineering, Bioinformatics, Data Science, or a related field
- Minimum of 5 years of hands on experience developing software for medical research, including work with electronic health records, medical imaging, or bioinformatics pipelines
- Proficiency in programming languages such as Python, R, or Julia, with experience using data science libraries and machine learning frameworks
- Strong background in statistical modeling, experimental design, or causal inference applied to clinical or biomedical data
- Familiarity with healthcare data standards (e.g., HL7, FHIR), regulatory frameworks (e.g., HIPAA, GDPR), and compliance requirements for medical data processing
- Experience with cloud platforms (e.g., AWS, GCP) or containerized environments for deploying research grade computational tools
Full Job Posting
Role Overview
- This is a contractual role focused on advancing medical research through technical implementation. The position requires applying computational expertise to design, develop, and evaluate algorithms and systems that support clinical and biomedical data analysis. The work directly contributes to impro
Key Responsibilities
- Design and implement technical frameworks to process, analyze, and interpret complex medical datasets including imaging, genomic, or electronic health records.
- Develop and validate machine learning models or statistical methods for predictive diagnostics, treatment optimization, or drug discovery applications.
- Collaborate with cross functional research teams to integrate computational solutions into clinical workflows and validate performance in real world settings.
- Ensure technical solutions comply with regulatory standards, data privacy requirements, and ethical guidelines in medical research.
- Document methodologies, results, and system architectures to support reproducibility, peer review, and regulatory submissions.
Required Skills & Qualifications
- Master’s degree or higher in Computer Science, Biomedical Engineering, Bioinformatics, Data Science, or a related field.
- Minimum of 5 years of hands on experience developing software for medical research, including work with electronic health records, medical imaging, or bioinformatics pipelines.
- Proficiency in programming languages such as Python, R, or Julia, with experience using data science libraries (e.g., Pandas, NumPy, Scikit learn) and machine learning frameworks.
- Strong background in statistical modeling, experimental design, or causal inference applied to clinical or biomedical data.
- Familiarity with healthcare data standards (e.g., HL7, FHIR), regulatory frameworks (e.g., HIPAA, GDPR), and compliance requirements for medical data processing.
- Experience with cloud platforms (e.g., AWS, GCP) or containerized environments for deploying research grade computational tools.
More About the Opportunity
- This role supports global initiatives in precision medicine by enabling scalable, reproducible research workflows. The position involves contributing to open source or proprietary systems that are used by clinicians, researchers, and data scientists worldwide. There is potential for long term collab
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