• Develop and maintain custom reports in Oracle HCM using SQL to support HR operations and analytics. • Write advanced SQL queries to extract and transform HR data from Oracle tables. • Analyze HR datasets for workforce insights (headcount, attrition, recruiting, talent & succession planning, engagement, team performance). • Ensure accuracy and consistency of HR data across systems. • Perform advanced analytics and modeling in Databricks using Python and SQL. • Leverage Databricks notebooks for data exploration, transformation, and machine learning. • Publish curated datasets from Databricks to BI tools (Power BI) for HR scorecards and executive reporting. • Apply Python and statistical techniques for predictive modeling (e.g., attrition forecasting, workforce planning). • Use Databricks ML and Delta Lake for scalable analytics. • Identify trends and deliver actionable insights to HR leadership. • Partner with HR leaders to translate business questions into data requirements. • Work closely with Data Engineering and Platform teams to ensure HR data is clean, standardized, and accessible. • Document processes and create user-friendly guides for HR stakeholders. • Understand and apply PII masking and compliance requirements for HR data. • Ensure adherence to privacy regulations (GDPR, CCPA) and internal security standards.

You’ll also help design and manage AI-powered agents that support analytical and forecasting workflows, with a strong emphasis on control, evaluation, and real operational value. This is a hands-on, senior role with clear ownership and accountability. Responsibilities - Build predictive, forecasting, and risk models to support policy decisions, agency strategy, and cash-flow planning. - Own the full production lifecycle of models, including deployment, monitoring, drift detection, and retraining. - Translate model outputs into decision-ready insights for policy, finance, and operations teams. - Partner closely with data engineering and product to ensure models are supported by scalable, reliable data pipelines. - Design and manage AI/LLM-based agents to automate or augment analytical workflows. - Define evaluation metrics, guardrails, and failure modes for agent-driven systems. - Improve model reliability, interpretability, and business impact as the platform scales.

• Map the Business of Healthcare workforce by developing a role and skills taxonomy • Gather and analyze trends in job postings, skills demand, hiring activity, compensation, and workforce pathways • Structure, clean, and classify AAPC’s existing member, role, and workforce data • Conduct interviews with employers, educators, and healthcare workforce leaders • Evaluate and integrate external labor datasets (BLS, ONET, job postings, surveys, etc.) • Use data to unlock insights and tell stories. Turn complex findings into clear, actionable insights that help guide key business decisions. • Produce research briefs, role profiles, workforce snapshots, and insights reports • Build early workforce dashboards using tools like Power BI or Tableau • Work closely with peers and leaders within AAPC to understand business needs and collaborate on designing impactful and actionable solutions. Lay the groundwork for scalable workforce insights, benchmarks, and data products • Partner with internal teams and external research partners to define the future of AAPC’s workforce intelligence capability

• Develop and validate pharmacometric models to support dose selection, trial design, and decision-making • Analyze and interpret complex pharmacokinetic (PK) and pharmacodynamic (PD) data • Author and review technical protocols, analysis plan, reports, and scientific publications • Review regulatory documents in area of expertise • Propose innovative quantitative pharmacology approaches and optimize modeling processes • Collaborate with clinical pharmacology, biostatistics, regulatory, and clinical development teams • Communicate modeling results and their implications to cross-functional teams and senior management • Oversee multiple pharmacometric projects, ensuring timely delivery of high-quality outputs • Manage project oversight, quality, and budget control