Overview In this role you will lead advanced analytics, statistical modeling, and AI initiatives to enable data-driven decision-making across Vizient. You will supervise a multidisciplinary data science team to deliver scalable models aligned with business objectives, governance, and ethical data use. You will shape the data science strategy and oversee model governance to advance cutting-edge ML methods and tangible client value. You will translate complex analyses into actionable insights for executives, collaborating across functions. This position offers enterprise impact and iterative development within an inclusive, development-focused culture.
Compensation / Benefits- comprehensive benefits plan
- incentive eligible
- competitive compensation range
- career development opportunities
- inclusive culture
- opportunity for impact across enterprise
Responsibilities- Provide strategic direction for ML and modeling initiatives and develop a roadmap for data-driven innovation
- Oversee design, development, validation, and deployment of statistical, econometric, and ML models for forecasting, risk assessment, and operational efficiency
- Establish robust model governance with documentation, version control, validation, and performance monitoring; ensure regulatory and ethical compliance
- Lead and mentor a multidisciplinary team of data scientists, ML engineers, and quantitative analysts; foster innovation and collaboration
- Collaborate with business leaders, IT, and analytics stakeholders to identify data science opportunities and translate results for executive decision-making
- Stay at the forefront of AI/ML technologies; evaluate and integrate new tools and methodologies to improve performance and scalability
Key requirements- Bachelor, Master, or Doctorate degree in Data Science, Statistics, Computer Science, Applied Mathematics, Engineering, Economics, or related quantitative field
- Expertise in machine learning, deep learning, and statistical modeling (e.g., regression, time series, NLP, ensemble methods, neural networks)
- Strong proficiency in Python and SQL; experience with cloud-based AI/ML platforms (AWS SageMaker, Azure ML, Databricks)
- Knowledge of ML Ops, model governance, and lifecycle management best practices
- Ability to translate business problems into analytical frameworks and deliver measurable outcomes
- Excellent leadership, communication, and stakeholder management; able to present to non-technical audiences
- Proven experience building and leading high-performing data science teams in a large, matrixed organization
- Familiarity with healthcare, financial, or operational analytics
- leadership
- communication
- stakeholder management
- machine learning
- deep learning
- statistical modeling
