> Markdown version of [/jobs/ext/3823679-manager-data-science](https://www.wearedevelopers.com/jobs/ext/3823679-manager-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager Data Science - **Company:** H. Lee Moffitt Cancer Center and Research Institute Hospital, Inc. - **Location:** Tampa, FL, United States - **Experience:** Experienced - **Salary:** $134,867.0 - $202,238.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Bioinformatics, Health Informatics, Clinical Data Repository, Cloud Computing, Databases, Information Engineering, Data Governance, Data Infrastructure, Decision Support Systems, Machine Learning, Natural Language Processing, Cloud Services, Enterprise Data Management, Feature Engineering, Information Technology, Data Analytics, Data Management, Data Pipelines - **Published:** October 18, 2026 - **Apply:** https://www.dice.com/job-detail/956f0bdd-85ce-46fd-8aeb-1ef4020186b5 ## About the Role * An experienced data science leader who can turn ambiguous business challenges into clear use cases, analytical questions, and prioritized work plans. * A collaborative people manager who coaches technical teams, establishes accountability, removes barriers, and builds an engaged, high-performing culture. * A strong communicator who can explain complex analytical concepts, risks, status, and outcomes to executive, business, and technical audiences. * A strategic partner with sound knowledge of data governance, analytics lifecycle management, privacy, security, compliance, and cross-functional delivery., * Master's degree in Data Science, Computer Science, Statistics, Bioinformatics, Health Informatics, Applied Mathematics, or a related field. * Minimum of seven (7) years of experience developing analytics products, models, tools, and systems in complex data environments, including three (3) years leading, mentoring, and supervising data scientists, analysts, and technical project teams. * Experience developing and implementing advanced analytical models and statistical or machine learning approaches. * Experience with enterprise data platforms, databases, cloud-based analytics environments, and regulated data environments with strong privacy, security, and compliance expectations. * Experience translating operational, clinical, or research needs into analytics solutions in partnership with technical and business stakeholders. * Strong knowledge of data science, statistical modeling, machine learning, analytics solution development, data governance, and analytics lifecycle management. * Excellent written and verbal communication, people leadership, coaching, performance management, cross-functional leadership, and agile or iterative project delivery skills. Preferred * Ph.D. in Data Science, Computer Science, Statistics, Bioinformatics, Health Informatics, Applied Mathematics, or a related field. * Experience in healthcare, academic medicine, biomedical research, or oncology-related analytics environments. * Experience supporting advanced analytics across clinical, research, or operational domains, including cloud-based services and production deployment patterns. * Experience with self-service analytics, cohort analysis, broad-use data products, health or clinical data structures, analytics strategy, roadmaps, and cross-functional governance. ## Description The Manager, Data Science leads the day-to-day activities of the data science team in the development, implementation, and support of advanced analytics products, models, and decision-support solutions that improve research, clinical, and operational outcomes. This role translates business needs into actionable analytics work, supervises data scientists, and ensures the delivery of high-quality, scalable, and compliant analytical solutions.The Manager will partner with the department Director, Information Technology, and business stakeholders to advance analytics capabilities, support the analytics platform, and operationalize data science solutions that create measurable organizational value. This role also helps turn ambiguous business scenarios into clear use cases, analytic questions, and prioritized work for the team. Lead advanced analytics that improve research, clinical, and operational outcomes. Join Moffitt Cancer Center's Data and AI Services division to lead the day-to-day work of a talented data science team. You will translate complex business needs into prioritized analytics work, guide the development of scalable and compliant models and decision-support solutions, and partner across Information Technology, research, clinical, and operational teams to create measurable organizational value., * Lead a data science team that develops, implements, and supports advanced analytics products, models, tools, and decision-support solutions. * Partner with Data and AI Services, Data Quality & Standards, AI Technology Delivery, Data Engineering, Enterprise Architecture, and business stakeholders to advance analytics capabilities and operationalize solutions. * Shape analytics architecture, reusable data products, governed workflows, and model monitoring practices that support reliable, scalable delivery. * Work in an office/remote environment while supporting analytics across clinical, research, and operational domains., * Lead and supervise data scientists, including day-to-day assignments, priorities, deliverables, performance expectations, coaching, onboarding, training, and professional development. * Oversee the design, development, testing, documentation, implementation, support, monitoring, evaluation, and continuous improvement of advanced analytical models and solutions. * Guide the selection of statistical techniques, machine learning approaches, feature engineering, natural language processing, and model operationalization practices based on business needs. * Partner with technical teams to support analytics architecture, data pipelines, curated datasets, reusable analytical assets, deployment, maintenance, and secure analytics workflows. * Engage leaders, project sponsors, and data consumers to define scope, prioritize work, align solutions to organizational goals, and improve decision support. * Contribute to analytics strategy, roadmaps, governance forums, and opportunities to expand the value and efficiency of data science across the organization.