Manager Data Science

Moffitt Cancer Center

7d•$134,867 - $202,238•Hybrid

About The Position

The Manager, Data Science leads the day-to-day activities of Moffitt Cancer Center’s data science team. The role oversees the development, implementation, support, and continuous improvement of advanced analytics products, models, tools, and decision-support solutions intended to improve research, clinical, and operational outcomes. The manager translates business needs and ambiguous challenges into clear analytical questions, use cases, and prioritized work, and ensures solutions are high-quality, scalable, and compliant. The position supervises and develops data scientists and partners with the department Director, Information Technology, Data and AI Services teams, and business stakeholders. It contributes to analytics strategy and architecture, reusable data products, governed workflows, model monitoring, and the operationalization of analytics solutions. The work supports clinical, research, and operational domains in an office/remote environment.

Requirements

Master’s degree in Data Science, Computer Science, Statistics, Bioinformatics, Health Informatics, Applied Mathematics, or a related field.
At least seven years of experience developing analytics products, models, tools, and systems in complex data environments.
At least three 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.

Nice To Haves

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.

Responsibilities

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.
Partner across Data and AI Services, Data Quality & Standards, AI Technology Delivery, Data Engineering, Enterprise Architecture, and business stakeholder groups to advance analytics capabilities and operationalize solutions.