Data Science Manager Jobs in Massachusetts

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Lilly’s RNA Therapeutics group is recruiting an accomplished computational genomics scientist to its Genomics Data Science & AI/ML team. The Director will lead a team of highly capable PhD-level scientists responsible for pipeline-facing genomics analysis of pre-clinical assets and for computational and AI/ML methods development. They will provide scientific and strategic leadership for the group, bringing additional depth in emerging machine learning and deep learning methods while developing the team’s strong existing bioinformatics and AI/ML talent. The role partners closely with an established, high-performing wet lab genomics team and with scientific leaders and project teams across RNA Therapeutics.

The ideal candidate is a scientific leader who measures success by the impact of their team and the scientific growth of the people they lead. They have a strong track record of applying bioinformatics and machine learning to large-scale genomics data and of translating those insights into decisions that advance pre-clinical programs. They bring current, credible depth in emerging AI/ML approaches for genomics. That depth lets them act as a technical thought partner to experimental and computational scientists already working at the frontier of the field: pressure-testing ideas, connecting the team to new methods, and helping the most promising work scale into portfolio impact. Applying genomics and bioinformatics to pipeline-facing work is central to this role. Delivering prompt, decision-grade analyses to project teams is as critical to success as computational innovation.

Key Responsibilities:

• Oversee the deployment of computational resources to enable drug discovery genomics efforts, such as sequencing-based high-throughput screening
• Lead, mentor, and grow a team of high-performing PhD-level data scientists
• Help set the team’s computational genomics and AI/ML strategy, aligning priorities with portfolio needs
• Build on the team’s existing AI/ML work, deepening its capability in emerging machine learning and deep learning methods and serving as a technical thought partner on method selection, model design, and evaluation
• Guide the translation of promising computational methods developed within the team into robust, scalable tools that support portfolio decisions
• Champion the adoption of new analytical approaches across RNA Therapeutics
• Foster an environment where team members contribute ideas and are recognized for their work
• Help the team navigate scientific and technical questions where no established precedent exists, and make the call when a decision is needed
• Partner with scientific leaders across RNA Therapeutics to guide the generation of large-scale genomics datasets purpose-designed to train, benchmark, and improve AI/ML models
• Ensure the team delivers rigorous, decision-grade analysis across modalities including 3'-RNA-seq, mRNA-seq, MPRA, single-cell genomics, spatial transcriptomics, CLIP-seq, and Perturb-seq
• Establish standards for reproducibility, quality control, and analytical rigor across the team’s analysis and ML workflows on cloud-based infrastructure
• Drive process optimization to increase the speed, reproducibility, and probability of technical success of genomics analysis across the portfolio
• Partner with an established wet lab genomics team to co-design experiments, interpret results, and troubleshoot
• Partner with project teams across RNA Therapeutics, providing computational insight that informs target and asset decisions
• Represent the team’s science to internal and external partners, and create opportunities for team members to present and publish their work
Build external collaborations and networks that bring new methods, collaborations, and talent to the team

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Basic Qualifications:

PhD in bioinformatics, computational biology, statistics, data science, machine learning, biophysics or a related scientific field, with a minimum of 4 years of relevant industry or academic leadership experience

Additional Skills/Preferences:

• Demonstrated experience leading and growing teams of scientists, including scientists doing original methods development
• Strong, current background in machine learning and deep learning for genomics (for example, sequence-to-function models, genomic foundation models, or perturbation response modeling), including designing datasets and evaluation strategies
• Deep knowledge of statistics, genetics, genomics, integrative analysis, and modeling
• Strong background analyzing large-scale genomics data across modalities such as 3'-RNA-seq, mRNA-seq, MPRA, single-cell genomics, spatial transcriptomics, CLIP-seq, and Perturb-seq
• Experience running genomics analysis in a pipeline-facing or production context, with an emphasis on reproducibility and quality control
• Strong working knowledge of cloud-based computing infrastructure for genomics and ML workflows

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Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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