Associate Director, Advanced Analytics

Responsibilities

• Collaborate with internal stakeholders and Advanced Analytics Analysts to provide creative solutions to current and anticipated business challenges, including strategic product innovation and data analytics enhancements.
• Partner with Advanced Analytics Operations to enhance pre-sales and pre-program launch analytics processes and initiatives that improve program value and impact.
• Serve as an analytics subject matter expert in partnership with Business Development.
• Translate complex analytical findings into meaningful business insights during client meetings, helping demonstrate program value and optimize future campaigns.
• Lead and develop a team of Statisticians and Managers, Advanced Analytics responsible for the quality, timeliness, and delivery of client measurement solutions.
• Mentor, guide, coach, and provide performance management to team members.
• Oversee the development, implementation, management, and validation of statistical analyses and methodologies for complex cross-functional projects utilizing advanced data modeling and analytical techniques.
• Serve as the primary analytics liaison for health system, EHR, and pharmacy network vendor partnerships.
• Examine, interpret, and communicate results of analytical initiatives to stakeholders across leadership, technology, sales, marketing, and product teams.
• Perform other duties as assigned.

Qualifications

• Advanced degree in Computer Science, Statistics, Mathematics, or a related field.
• 10+ years of experience monitoring, managing, manipulating, and deriving insights from data.
• Minimum 3 years of experience leading strategic projects.
• Experience leading and developing high-performing analytics teams.
• Strong understanding of data mining principles, including: Predictive analytics, Mapping, Multivariate analysis, Significance testing, Regression analysis, Decision trees.
• Experience collecting and integrating data from multiple on-premises and cloud-based data sources.
• Experience using statistical programming languages such as SAS.
• Strong SQL skills with the ability to manipulate data and build statistical models.
• Ability to perform complex querying involving multiple tables and subqueries.
• Strong analytical, problem-solving, and communication skills.
• Ability to translate technical analyses into actionable business recommendations.