Associate Director – Biomarker Data Sciences

Responsibilities

• Develop and apply novel or existing computational methods for patient segmentation from multimodal clinical and omics datasets for various treatment modalities in partnership with Translational, Clinical and Statistical Scientists.
• Partner with lead and protocol statisticians in writing, reviewing and executing protocols and statistical analysis plans (SAP) for biomarkers and diagnostics, highlighting the biomarker strategy for clinical drug development.
• Defend biomarker analysis plans at internal reviews and provide reviews of complex biomarker-related study and analysis plans.
• Take a lead role on biomarker-related analysis plans and analyses; and revise as needed as data emerges.
• Coordinate biomarker analyses on datasets from BMS clinical trials and real-world data cohorts.
• Plan and perform relevant and innovative statistical analyses of high-dimensional (e.g. gene expression, sequencing) data generated by cutting edge technologies.
• Execute and contribute to the scientific and statistical strategy of drug development, including development of predictive biomarker(s) and precision medicine.
• Collaborate with biomarker scientists in planning and executing experiments to optimize and validate biomarker assays for clinical trial usage.
• Develop, implement, and apply state-of-the-art algorithms to address key business problems and drive the implementation of innovative statistical methods in support of biomarker strategy.
• Formulate, implement, test, and validate predictive models and implement efficient automated processes for producing modeling results at scale.
• Manage and coordinate resources to produce quality deliverables within timelines for competing priorities.
• Contribute to internal and external scientific communities, bringing forth innovative approaches to biomarkers and drug development.
• Develop and advise team members.
• Effectively communicate the GBDS Mission and Vision in a fashion that generates pride, excitement and commitment within GBDS.
• Enable a culture of inclusiveness, respect for diversity, compliance with process and allows for the questioning and challenging of others in a respectful and constructive manner.
• Provide support and leadership to address health authority requests, publications, presentations, and other public releases of information.

• Ph.D. in a relevant quantitative field (i.e. Computational Biology, Biostatistics, Statistics, Computer Science, etc.) and 6+ years of academic/industry experience or Master’s Degree in a relevant quantitative field and 8+ years of industry experience.
• Strong experience in the analysis of data generated by one or more
  -omics or molecular assays is required.
• Knowledge of molecular biology, understanding of disease pathways.
• Strong experience in biomarker data analysis with data generated from clinical trials, or electronic health records.
• Experience in modeling methods particularly in their application to pharma R&D.
• Experience in the application of AI/ML, and proficient in SQL, Python, and R and cloud platforms.
• Experience developing statistical and machine learning models on high dimensional and high throughput data for time to event data and longitudinal outcomes.
• Perspective in leveraging innovative approaches to expedite drug development and address the complexities of emerging data.
• Demonstrated ability to lead a team.
• Ability to work both independently and collaboratively, and to handle several concurrent, fast-paced projects.
• Strong problem-solving and collaboration skills, and rigorous and creative thinking.
• Excellent communication, data presentation, and visualization skills.
• Capable of establishing strong working relationships across the organization.