

Machine Learning Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior ML/Bioinformatics Data Scientist on a 1-year contract, paying $50-$63/hour. It requires a PhD in a quantitative field, 5+ years of experience with biomedical datasets, and proficiency in Python/R. Remote work during PST hours.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
504
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ποΈ - Date discovered
September 4, 2025
π - Project duration
More than 6 months
-
ποΈ - Location type
Remote
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
San Francisco Bay Area
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π§ - Skills detailed
#Data Integration #Statistics #Mathematics #Computer Science #Documentation #ML (Machine Learning) #R #Python #Data Manipulation #Datasets #Data Science
Role description
Title: Senior ML/Bioinformatics Data Scientist (Contract)
Location: Remote (must be available during PST business hours)
Minimum Education: PhD degree in quantitative field (Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics)
Pay: $50-$63/hour
Contract: 1 year, with potential extension
Position Overview
We are seeking an experienced ML/Bioinformatics Data Scientist to join our computational sciences team on a high-impact contract engagement. This role focuses on developing advanced machine learning solutions for healthcare applications, specifically working with complex multi-modal datasets to build predictive models that support clinical decision-making and patient safety initiatives.
Key Responsibilities
β’ Design and implement machine learning pipelines for analyzing complex biomedical datasets including clinical, genomic, and laboratory data.
β’ Lead data integration and harmonization efforts across multiple data sources and formats.
β’ Develop predictive models to identify patient risk factors and safety profiles for therapeutic interventions.
β’ Engineer novel features from diverse data types to enhance model performance and clinical interpretability.
β’ Collaborate with cross-functional teams including biologists, clinicians, statisticians, and product stakeholders.
β’ Create comprehensive documentation and present findings to technical and non-technical audiences.
Required Qualifications
β’ PhD in quantitative discipline (Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics, or related field).
β’ 5+ years of hands-on experience applying machine learning methods to multi-modal biomedical datasets.
β’ Expert proficiency in Python and/or R with extensive experience in data manipulation, statistical modeling, and ML frameworks.
β’ Proven experience working with omics data, clinical datasets, and/or medical imaging data.
β’ Strong background in biostatistics including survival analysis and time-to-event modeling.
β’ Excellent written and verbal communication skills with ability to explain technical concepts to diverse audiences.
β’ Track record of peer-reviewed publications in relevant fields.
This job description is a complete list of all desired skills, but not all are required. We strongly encourage candidates who have some of the skills to apply. We look forward to a conversation to learn more about you!
Title: Senior ML/Bioinformatics Data Scientist (Contract)
Location: Remote (must be available during PST business hours)
Minimum Education: PhD degree in quantitative field (Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics)
Pay: $50-$63/hour
Contract: 1 year, with potential extension
Position Overview
We are seeking an experienced ML/Bioinformatics Data Scientist to join our computational sciences team on a high-impact contract engagement. This role focuses on developing advanced machine learning solutions for healthcare applications, specifically working with complex multi-modal datasets to build predictive models that support clinical decision-making and patient safety initiatives.
Key Responsibilities
β’ Design and implement machine learning pipelines for analyzing complex biomedical datasets including clinical, genomic, and laboratory data.
β’ Lead data integration and harmonization efforts across multiple data sources and formats.
β’ Develop predictive models to identify patient risk factors and safety profiles for therapeutic interventions.
β’ Engineer novel features from diverse data types to enhance model performance and clinical interpretability.
β’ Collaborate with cross-functional teams including biologists, clinicians, statisticians, and product stakeholders.
β’ Create comprehensive documentation and present findings to technical and non-technical audiences.
Required Qualifications
β’ PhD in quantitative discipline (Computer Science, Computational Biology, Bioinformatics, Statistics, Mathematics, or related field).
β’ 5+ years of hands-on experience applying machine learning methods to multi-modal biomedical datasets.
β’ Expert proficiency in Python and/or R with extensive experience in data manipulation, statistical modeling, and ML frameworks.
β’ Proven experience working with omics data, clinical datasets, and/or medical imaging data.
β’ Strong background in biostatistics including survival analysis and time-to-event modeling.
β’ Excellent written and verbal communication skills with ability to explain technical concepts to diverse audiences.
β’ Track record of peer-reviewed publications in relevant fields.
This job description is a complete list of all desired skills, but not all are required. We strongly encourage candidates who have some of the skills to apply. We look forward to a conversation to learn more about you!