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Sr Translational Med Scientist; Women's Health

Job in Yonkers, Westchester County, New York, 10701, USA
Listing for: Remote Jobs
Full Time position
Listed on 2026-10-03
Job specializations:
  • Research/Development
    Clinical Research, Data Scientist, Research Scientist
  • Healthcare
    Clinical Research, Data Scientist
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below
Position: Sr Translational Med Scientist (Women's Health)

Position Summary
We are seeking a Clinical-Translational Scientist, (TMED) with a passion for Women’s Health research and expertise in medical genetics and genomics. This individual will collaborate closely with cross-functional teams and external partners, using their expertise in clinical research and genomics to drive actionable insights, and guide the development of research projects and scientific publications. This position offers a unique opportunity to blend biostatistics, clinical research, and translational medicine in a rapidly evolving environment.

Key Responsibilities
  • In Depth Knowledge of Internal Women’s Health Clinical and Commercial Data
    • Serve as the primary point of contact for all internal clinical and commercial data relating women’s health products and clinical trials.
    • Implement structures and processes for curating and managing datasets
    • Track the types and sources of data (e.g., EHR, real-world data, commercial laboratory data, clinical trials) to optimize use for medical education, publications, and product development.
    • Reinforce processes for data governance, ensuring data accuracy, quality, and regulatory compliance.
  • Data Analysis & Study Planning
    • Design and execute genomic and clinical analyses to explore biological, scientific, and clinical questions in women’s health.
    • Support the planning of studies collaborating with clinical operations to ensure appropriate data capture, study design, and protocol development.
    • Monitor the research landscape and evaluate emerging technologies and competitive trends
  • Collaborate with Cross-Functional Teams Work side‑by‑side with data scientists and biostatistics team to perform robust analyses on women’s health datasets.
    • Partner with internal teams such as clinical operations, research & development, biostatistics, product management, external site investigators, and key opinion leaders to ensure efficient execution of studies and trials.
  • Publication & Communication
    • Collaborate with relevant stakeholders and key opinion leaders on the preparation of abstracts, posters, and manuscripts for peer-reviewed publications and academic conferences.
    • Present results to internal and external audiences, including clinicians, academic partners, and cross‑functional stakeholders.
    • Translate technical findings into clear, actionable insights for decision‑makers across the organization.
  • Compliance & Privacy
    • Handle PHI (Protected Health Information) and ensure compliance with HIPAA regulations and Natera policies.
    • Maintain a current status on organizational training requirements and pass a post- offer criminal background check.
  • Qualifications
    • Ph.D. in Clinical Science, Molecular Biology, Genomics, Bioinformatics, Genetics, or related disciplines.
    • Strong scientific foundation in molecular genomics perspectives, preferably in the women’s health space.
    • Demonstrated experience working with genetic data and nomenclature. Variant curation experience and knowledge a plus.
    • Experience working with real-life clinical data (e.g., EMR, LIMS, etc.) and knowledge of clinical parameters and variable definitions.
    • Demonstrated project management experience is a must
    • Demonstrated experience working with external collaborators/KOLs a must.
    • Proficiency in data mining, data curation, statistical analysis tools, and methodologies.
    • Expertise in R programming, including packages such as ggplot2, data.table, and Bioconductor.
    • Familiarity with querying relational databases using SQL.
    • Demonstrated experience with predictive modeling, epidemiological methodology, clinical observational and retrospective study design. Familiarity with machine learning algorithms, computational modeling, or other advanced data science methodologies is beneficial.
    Knowledge, Skills, and Abilities
    • Clinical Research &…
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