Role SummaryThe Vice President Data & Analytics is the enterprise leader responsible for Anovo's data, analytics and AI strategy, capabilities and operating model. This leader owns data architecture and data governance for Anovo's internal and customer-facing digital platforms and sets the vision and roadmap for data, analytics and AI across the company. Anovo is a specialty pharmacy focused on rare disease and orphan drug therapies, so trusted data, analytics, security and compliance are foundational to patient care, client service, operational performance and growth.
This role will lead a multidisciplinary team spanning data engineering/architecture, data analysts and data scientists while partnering with department heads and executive leadership to identify growth opportunities, improve operational and financial performance, demonstrate client value, track key performance indicators (KPIs), and enable informed enterprise decision-making.
The below is intended to describe the general content of and requirements for the performance of this job and is not to be construed as an exhaustive statement of essential functions, responsibilities, or requirements.
Key ResponsibilitiesYou are accountable for how Anovo's data is designed, governed, and turned into decisions. The role has five areas of ownership.
Business & Enterprise Analytics- Set the multi-year data and analytics strategy and roadmap, aligned to Anovo's business and technology priorities.
- Define the operating model, standards, and investment case for data across the organization.
- Serve as a strategic advisor to the Executive Committee and senior leaders on data, analytics and AI opportunities, risks and investments.
- Partner with executive and functional leaders to identify opportunities where data, analytics and AI can improve revenue growth, client value, patient outcomes, operational performance and financial results.
- Influence enterprise priorities by translating technical possibilities into business cases, financial impact and measurable outcomes.
- Communicate complex analytical and technical concepts clearly to both technical and non-technical audiences.
- Translate complex business questions into analytical frameworks, measurable outcomes and actionable recommendations.
- Establish a portfolio of enterprise analytics use cases, sequence delivery based on expected value and feasibility, and track whether completed initiatives achieve their intended outcomes.
- Develop predictive and prescriptive analytics capabilities that move the organization beyond descriptive reporting toward proactive decision-making.
Data architecture- Own the end-to-end data architecture for the Aperture platform, including data models, pipelines, storage, integration, and reporting layers.
- Set design standards for PostgreSQL and AWS data services covering performance, scalability, resiliency, security, and cost.
- Partner with enterprise architecture, security, and validation leads so the data design fits the wider platform.
- Evaluate new tools and patterns, and build data foundations that are ready for advanced analytics and machine learning.
AI Strategy & Enablement- Develop and execute Anovo's enterprise AI strategy in partnership with Technology and business leadership.
- Identify and prioritize AI and machine-learning opportunities that improve patient experience, operational efficiency, client value and business performance.
- Establish the data, governance and technology foundations required to deploy AI responsibly and at scale.
- Partner with Legal, Compliance, Security and business leaders to establish appropriate standards for responsible AI, data privacy, security and model governance.
- Evaluate emerging AI technologies and determine where Anovo should build, buy or partner.
Data governance- Define the enterprise data-quality framework, including standards for accuracy, completeness, timeliness, consistency and reliability.
- Implement controls, thresholds and monitoring that measure adherence to data-quality standards for critical data assets.
- Assign accountable owners and establish escalation and remediation processes for material data-quality issues.
- Build and run the data governance program: ownership and stewardship, data quality standards, metadata and lineage, retention, and access controls.
- Ensure the handling of protected health information (PHI) meets HIPAA and other regulatory requirements, working with Compliance, Security, and Legal.
- Establish trusted enterprise data products and standardized datasets that serve as authoritative sources for reporting, analytics, AI and operational decision-making.
- Establish common enterprise definitions, metrics and business rules to create a consistent source of truth across functions.
- Drive adoption of governed, reusable data assets rather than duplicative, function-specific reporting solutions.
Team leadership- Lead a multidisciplinary team spanning data engineering, data architecture, analytics and data science.
- Manage the enterprise Data & Analytics delivery portfolio, balancing strategic initiatives, operational needs, technical debt, regulatory requirements and emerging opportunities across available resources and timelines.
- Define and apply transparent criteria for approving analytics, data and AI investments based on expected business value, risk, resource requirements and alignment with enterprise strategy.
- Manage the team's budget, vendors, and capacity planning.
Business partnership, KPIs, and efficiency- Partner with Commercial, Client Services and Customer Success leaders to define the business questions, measures and analytical insights needed to demonstrate client value, patient outcomes and program performance.
- Develop scalable, governed capabilities for delivering customer-facing reports, dashboards, analytics and data products.
- Translate Anovo's data assets and analytical findings into differentiated insights that strengthen client relationships, demonstrate program value and support growth.
- Define, track, and publish KPIs, and own the executive and departmental dashboards in Power BI.
- Improve efficiency by automating reporting, retiring redundant reports, and moving teams toward self-service analytics.
QualificationsThe strongest candidates combine hands-on data architecture depth with proven leadership of multi-disciplinary teams.
Required- Bachelor's degree in computer science, information systems, data science, statistics, or a related field. An advanced degree is preferred.
- 12+ years of experience in data, analytics, or data engineering, including 7+ years in leadership roles.
- Proven experience designing and owning enterprise data architecture on AWS and PostgreSQL, including data modeling, warehousing, and ETL/ELT pipelines.
- Advanced SQL skills and hands-on experience delivering enterprise reporting in Power BI.
- Experience building and running a data governance program covering data quality, stewardship, lineage, metadata, and access controls.
- Experience leading data analysts, data architects, and data scientists, and developing them as individual contributors and managers.
- A track record of setting data strategy and vision and delivering it as an executed roadmap.
- Strong executive communication skills, with the ability to turn business questions into measurable KPIs.
Preferred- Experience in healthcare, pharmacy, life sciences, or another regulated industry.
- Working knowledge of HIPAA and the handling of PHI, and familiarity with validated-system requirements such as 21 CFR Part 11.
- Experience enabling machine learning and generative AI use cases on governed data, ideally on AWS, or experience with Mosaic and Snowflake.
- Experience with cloud-native platforms such as Kubernetes on AWS (EKS) and modern CI/CD practices.
This description is intended to be only a general outline of major activities. It is expected that the employee performs these and any other activities which may be assigned, or which may occur in the normal course of work. It description is not a contract or guarantee of employment. 
