Lead the complete Next Best Action delivery lifecycle, from strategy and design through development, testing, deployment, measurement, and ongoing optimization.
Translate business objectives into actionable inclusion and exclusion criteria, targeting logic, and decision strategies.
Develop and maintain SQL and BigQuery based data pipelines to support campaign targeting, sizing, execution, and reporting.
Build and refine measurement frameworks to evaluate campaign effectiveness, business outcomes, and member engagement.
Conduct ad hoc analyses to uncover optimization opportunities and inform stakeholder decisions.
Configure and support NBA implementations within Pega, ensuring launch readiness and process validation.
Perform campaign QA, monitor operations, and resolve issues to ensure successful NBA execution.
Collaborate with business, product, and technology teams to drive data-informed decisioning and recommendation strategies.
Support experimentation and test-and-learn initiatives, including A/B testing and performance measurement.
Leverage predictive models, AI/ML, and LLM-based inference where appropriate to enhance decisioning effectiveness.
Requirements
Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field.
Proficiency in SQL
Experience with Google Cloud Platform (GCP)
Expertise with BigQuery
Python programming skills
Hands-on experience designing and managing BigQuery pipelines and analytical workflows
Strong understanding of campaign targeting, audience segmentation, recommendation systems, and decision strategies
Experience designing and implementing measurement frameworks and performance analytics
Ability to translate complex business problems into scalable analytical solutions
Technologies
SQL
Google Cloud Platform (GCP)
BigQuery
Python
Pega
Preferred Qualifications
Experience in healthcare analytics, member engagement, or payer organizations
Knowledge of experimentation methodologies, uplift modeling, ranking/recommendation systems, and product analytics
Exposure to machine learning and Generative AI and LLM inference use cases
Experience supporting operational campaign delivery and production decisioning environments
Experience with Pega Decisioning or related campaign orchestration platforms
Strong experience in NBA, campaign management, decisioning, or customer engagement analytics
