Associate Director, Clinical Data Integration & AI Programming

The posting, as Acadia Pharmaceuticals Inc. wrote it

About Acadia Pharmaceuticals

Acadia is committed to turning scientific promise into meaningful innovation that makes the difference for underserved neurological and rare disease communities around the world. Our commercial portfolio includes the first and only FDA-approved treatments for Parkinson’s disease psychosis and Rett syndrome. We are developing the next wave of therapeutic advancements with a robust and diverse pipeline that includes mid- to late-stage programs in Alzheimer’s disease psychosis and Lewy body dementia psychosis, along with earlier-stage programs that address other underserved patient needs. At Acadia, we’re here to be their difference.

Position Summary

The Associate Director is a hands-on technical role responsible for automating how clinical data are integrated across assigned compounds and studies, and for building the reusable R and Python dashboards and data review tools that make those data usable by study teams. Working in R, Python, SQL, and APIs on the Posit platform, the role builds automated ingestion pipelines with incoming quality and congruency checks, maps disparate source structures into a standardized analysis-ready data model and delivers validated dashboards and review tools built on that foundation. It additionally evaluates and implements applied AI and generative AI capabilities where they measurably improve data processing, quality review, or programming productivity, always under human oversight and in accordance with regulations, SOPs, and data privacy requirements.

Primary Responsibilities

Clinical Data Integration and Automation

• Designs, builds, and maintains automated pipelines that ingest clinical data from EDC systems, central laboratories, eCOA and IRT vendors, safety systems, and other external providers at defined refresh frequencies, with scheduling, versioning, audit trails, processing logs, and failure alerting
• Owns the standardized cross-study and cross-compound clinical data model that harmonizes source structures, terminology, and variables into consistent, analysis-ready form, and establishes metadata-driven mapping specifications so new studies and vendors onboard without rebuilding pipelines
• Develops automated incoming data quality and congruency checks, including completeness, structural conformance, visit and date consistency, cross-domain reconciliation, duplicates, and outliers, and routes actionable exception outputs to Data Management and study teams
• Automates laboratory, SAE, eCOA, and IRT reconciliation workflows and develops congruency flags that identify discrepancies across studies, compounds, and source systems
• Develops algorithms and data feeds supporting risk-based monitoring and centralized data surveillance
• Builds controlled APIs and data access components that provide consistent, governed access to standardized clinical data for dashboards and downstream programming

R and Python Dashboards and Data Review Tools

• Designs, develops, vali

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m, or any basis protected under federal, state or local law.

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