Director of Data Science and Bioinformatics

Accountabilities:

• • Define and build the Bioinformatics function within the Data Science development organization, identifying technical capability and tooling gaps and establishing a roadmap for scalable genomics-based algorithm development.
  • Establish and maintain quality standards for pipelines and algorithms, including technical review processes, validation frameworks, reproducibility requirements, and documentation practices.
  • Architect and oversee scalable AWS-based infrastructure supporting data-intensive bioinformatics workloads and reliable deployment of next-generation sequencing algorithms.
  • Implement MLOps capabilities and automated validation frameworks that improve the reliability, reproducibility, monitoring, and deployment of computational algorithms into clinical production.
  • Partner closely with Research, Product Development, Laboratory Operations, Engineering, and Quality teams to deliver stable, scalable computational pipelines and support successful productization.
  • Lead, mentor, recruit, and develop a high-performing team of bioinformaticians and data scientists, establishing clear technical standards, accountability, and operational ownership.
  • Build technical depth and organizational capabilities that support expanding product portfolios and increasingly sophisticated genomic data and algorithm requirements.
  • Identify opportunities to improve infrastructure, workflows, tooling, and development practices while independently driving execution in a rapidly evolving technical environment.
  • Establish strong cross-functional alignment through clear technical communication, direct engagement, and data-driven decision-making.

  Requirements:

  • Master’s degree or Ph.D. in a quantitative technical discipline such as Bioinformatics, Biostatistics, Computer Science, Physics, Applied Mathematics, or a related field.
  • At least 10 years of professional experience in Data Science, Bioinformatics, or a closely related technical discipline, including a minimum of 5 years of direct people-management experience.
  • Demonstrated experience architecting AWS cloud infrastructure for data-intensive bioinformatics workloads and next-generation sequencing pipeline execution.
  • Strong understanding of bioinformatics, genomic data processing, computational pipelines, and data science methodologies.
  • Demonstrated ability to identify technical and organizational capability gaps, establish scalable solutions, and independently drive execution.
  • Proven experience developing and delivering computational pipelines that support commercial or production-grade products.
  • Strong leadership and talent-development capabilities, with experience building, mentoring, and retaining high-performing technical teams.
  • Excellent communication and collaboration skills, with the ability to establish alignment across Research, Engineering, Product Development, Laboratory Operations, and Quality functions.
  • Experience working within regulated environments such as CLIA, FDA, or ISO frameworks is preferred.
  • Familiarity with MLOps and pipeline technologies such as MLflow, Nextflow, WDL, and Docker is advantageous.
  • Advanced knowledge of statistical inference, machine learning, and genomic data processing is preferred.

  Benefits:

  • Salary range: $178,200–$222,800 USD for the remote U.S. position, with actual compensation determined by factors including skills, experience, certifications, and location.
  • Comprehensive medical, dental, and vision insurance for eligible employees and dependents.
  • Life and disability insurance.
  • Fertility and fertility-care benefits, including access to testing benefits for employees and immediate family members.
  • 401(k) retirement benefits.
  • Pregnancy and baby-bonding leave.
  • Commuter benefits.
  • Employee referral program.
  • Opportunity to work remotely within the United States.
  • Collaborative environment with opportunities to work alongside experienced professionals across data science, genetics, medicine, laboratory science, engineering, and related disciplines.
  • Inclusive workplace committed to diverse backgrounds, experiences, perspectives, and abilities.