Merck
Senior Director, Computational Biology (Cardiometabolic Drug Discovery Data Scie
Merck, South San Francisco, California, United States, 94080
Senior Director, Computational Biology Lead
The Precision Genetics group within Data, AI and Genome Sciences (DAGS) is recruiting a Senior Director, who will serve as the computational biology lead for Cardiometabolic Drug Discovery Data Science. We are seeking an experienced computational biologist with a proven track-record in applying human genetics to generate target/biomarker hypotheses and patient stratification strategies. This role will lead a team of bioinformaticians and data scientists to apply cutting edge AI/ML approaches to leverage our company's investments in human genetics and other multimodal data to support drug discovery in the cardiometabolic disease space. This work will help to inform discovery, translational medicine, companion diagnostics and clinical research. The Senior Director will also serve as a strategic partner to our discovery colleagues in Cardiometabolic Discovery Research. This is a hands-on leadership role, implementing rigorous data analysis practices, aligning resources based on scientific priorities, and mentoring and developing team members, as well as operate in a highly collaborative environment, partnering with peers across multiple locations and in the broader scientific community. In this exciting role, you will: Manage, mentor and hire outstanding team members responsible for creating an end-to-end computational biology strategy and support discovery programs in Cardiometabolic diseases. Create the strategy and process for evaluating therapeutic targets and precision biomarkers from the perspective of genetics, causal disease biology drawing upon a combination of public and proprietary resources. Collaborate with scientists and clinicians to create the data science strategy for Cardiometabolic disease targets in discovery, being innovative and foreseeing the path to clinical trial. Leverage scRNASeq to contextualize target gene expression in the context of cell-types, disease biology and cardiac phenotypes. Evaluate opportunities across potential indications using diverse data sources. Stay up to date on the application of AI/ML to cardiometabolic drug discovery strategy to prioritize target portfolio based on biological insights. Proactively identify biomarker discovery strategies to support discovery program and generate patient stratification strategies using cutting edge AI/ML methods. Communicate complex AI/ML strategies and insights derived from biological data to stakeholders via compelling visualization using state-of-the-art best practice. Identify appropriate public data sources to facilitate and augment AI/ML model building. Tackle complex projects, anticipate, and overcome challenges, and forecast timelines for deliverables to support pipeline objectives. Supervise the work of junior colleagues when appropriate. Collaborate with experimental scientists in a matrixed environment to develop research plans, optimize resource allocation, and maximize efficiencies to best execute on programs. Clearly communicate results to project teams, our company's scientific community, and the external scientific community through internal documents, presentations, and publications in leading journals. Qualifications: Education: Ph.D. in computational biology or related field and a minimum of 10 years of combined research experience in academia/pharma. Required Experience and Skills: Proven track record working in a cardiometabolic computational team. Prior experience mentoring or developing junior data scientists. Hands-on experience in integrating data from genetics, proteomics, single-cell transcriptomics and high-dimensional molecular data to derive insights into causal disease mechanism. Ability to code in R/Python and establish best practices for reproducible data analyses. Strong ability to work and influence in complex matrixed organizations. Excellent oral and written communication skills. Ability to establish and maintain productive cross-site and high caliber external collaborations. Preferred Experience and Skills: Experience is establishing academic and consortia partnerships. Familiarity with animal models of cardiometabolic diseases. Familiarity with CRISPR approaches for target validation. The salary range for this role is $231,400.00 - $364,200.00. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable. We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days.
The Precision Genetics group within Data, AI and Genome Sciences (DAGS) is recruiting a Senior Director, who will serve as the computational biology lead for Cardiometabolic Drug Discovery Data Science. We are seeking an experienced computational biologist with a proven track-record in applying human genetics to generate target/biomarker hypotheses and patient stratification strategies. This role will lead a team of bioinformaticians and data scientists to apply cutting edge AI/ML approaches to leverage our company's investments in human genetics and other multimodal data to support drug discovery in the cardiometabolic disease space. This work will help to inform discovery, translational medicine, companion diagnostics and clinical research. The Senior Director will also serve as a strategic partner to our discovery colleagues in Cardiometabolic Discovery Research. This is a hands-on leadership role, implementing rigorous data analysis practices, aligning resources based on scientific priorities, and mentoring and developing team members, as well as operate in a highly collaborative environment, partnering with peers across multiple locations and in the broader scientific community. In this exciting role, you will: Manage, mentor and hire outstanding team members responsible for creating an end-to-end computational biology strategy and support discovery programs in Cardiometabolic diseases. Create the strategy and process for evaluating therapeutic targets and precision biomarkers from the perspective of genetics, causal disease biology drawing upon a combination of public and proprietary resources. Collaborate with scientists and clinicians to create the data science strategy for Cardiometabolic disease targets in discovery, being innovative and foreseeing the path to clinical trial. Leverage scRNASeq to contextualize target gene expression in the context of cell-types, disease biology and cardiac phenotypes. Evaluate opportunities across potential indications using diverse data sources. Stay up to date on the application of AI/ML to cardiometabolic drug discovery strategy to prioritize target portfolio based on biological insights. Proactively identify biomarker discovery strategies to support discovery program and generate patient stratification strategies using cutting edge AI/ML methods. Communicate complex AI/ML strategies and insights derived from biological data to stakeholders via compelling visualization using state-of-the-art best practice. Identify appropriate public data sources to facilitate and augment AI/ML model building. Tackle complex projects, anticipate, and overcome challenges, and forecast timelines for deliverables to support pipeline objectives. Supervise the work of junior colleagues when appropriate. Collaborate with experimental scientists in a matrixed environment to develop research plans, optimize resource allocation, and maximize efficiencies to best execute on programs. Clearly communicate results to project teams, our company's scientific community, and the external scientific community through internal documents, presentations, and publications in leading journals. Qualifications: Education: Ph.D. in computational biology or related field and a minimum of 10 years of combined research experience in academia/pharma. Required Experience and Skills: Proven track record working in a cardiometabolic computational team. Prior experience mentoring or developing junior data scientists. Hands-on experience in integrating data from genetics, proteomics, single-cell transcriptomics and high-dimensional molecular data to derive insights into causal disease mechanism. Ability to code in R/Python and establish best practices for reproducible data analyses. Strong ability to work and influence in complex matrixed organizations. Excellent oral and written communication skills. Ability to establish and maintain productive cross-site and high caliber external collaborations. Preferred Experience and Skills: Experience is establishing academic and consortia partnerships. Familiarity with animal models of cardiometabolic diseases. Familiarity with CRISPR approaches for target validation. The salary range for this role is $231,400.00 - $364,200.00. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee's position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable. We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days.