[Remote] Bioinformatics Scientist – Mortality Risk Modeling
Key Details • Experience Level:
Senior (5 to 8 years), Expert & Leadership (9+ years) • Job Type: Full Time • Visa Sponsorship: Unknown • Industries: Insurtech, Life Insurance, Health Technology Responsibilities
The Bioinformatics Scientist will design and execute studies using novel data to improve mortality risk prediction. They will develop and validate machine learning and statistical models for mortality scoring, and partner with Data Science and Engineering to bring models into production.
This role also involves collaborating with Actuarial and Underwriting teams to align on validation and impact, and contributing to the methodology and roadmap of a modern, scalable mortality modeling system. Requirements Candidates must possess an MS or PhD in Bioinformatics, Statistics, Biostatistics, Applied Mathematics, Data Science, or a similar field, with 4+ years of experience in applied statistical modeling or machine learning. Proficiency in Python or R and relevant libraries is essential, along with experience working with medical ontologies like ICD, SNOMED, LOINC, or OMOP CDM.
Experience in survival modeling, biomarker analysis, or health risk scoring is preferred, as is the ability to thrive in cross-functional settings and communicate technical findings clearly to diverse audiences. Skills • Bioinformatics • Survival Analysis • Machine Learning • Predictive Analytics • Data Science • Actuarial Science • Underwriting • Biomarkers • Medical History • Computational Health • Applied Statistics Apply tot his job
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Senior (5 to 8 years), Expert & Leadership (9+ years) • Job Type: Full Time • Visa Sponsorship: Unknown • Industries: Insurtech, Life Insurance, Health Technology Responsibilities
The Bioinformatics Scientist will design and execute studies using novel data to improve mortality risk prediction. They will develop and validate machine learning and statistical models for mortality scoring, and partner with Data Science and Engineering to bring models into production.
This role also involves collaborating with Actuarial and Underwriting teams to align on validation and impact, and contributing to the methodology and roadmap of a modern, scalable mortality modeling system. Requirements Candidates must possess an MS or PhD in Bioinformatics, Statistics, Biostatistics, Applied Mathematics, Data Science, or a similar field, with 4+ years of experience in applied statistical modeling or machine learning. Proficiency in Python or R and relevant libraries is essential, along with experience working with medical ontologies like ICD, SNOMED, LOINC, or OMOP CDM.
Experience in survival modeling, biomarker analysis, or health risk scoring is preferred, as is the ability to thrive in cross-functional settings and communicate technical findings clearly to diverse audiences. Skills • Bioinformatics • Survival Analysis • Machine Learning • Predictive Analytics • Data Science • Actuarial Science • Underwriting • Biomarkers • Medical History • Computational Health • Applied Statistics Apply tot his job
Apply tot his job
Apply To this Job