[Hiring] Associate Director, Clinical Data Integration & AI Programming @Acadia Pharmaceuticals Inc.

Role Description

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.

Qualifications

• Bachelor’s degree in statistics, biostatistics, computer science, data science, biomedical informatics or a related science field.
• Targeting 10 years of progressively responsible experience in statistical programming, clinical programming, clinical data engineering, or clinical analytics, preferably in a pharmaceutical or biotech environment.
• Advanced hands-on R programming, including Shiny, tidyverse, data.table, R Markdown/Quarto, package development, modular application design, and reproducible workflows.
• Strong hands-on Python for data ingestion, transformation, automation, analytics, and application development.
• Strong SQL proficiency and experience building and consuming REST APIs.
• Demonstrated experience developing and deploying interactive clinical dashboards, patient profiles, data review tools, or study monitoring applications used by study teams.
• Demonstrated experience designing automated ingestion, transformation, mapping, validation, and refresh processes for structured and semi-structured clinical data.
• Experience standardizing and integrating EDC, laboratory, eCOA, safety, IRT, and operational data across multiple studies or programs.
• Experience with Posit/RStudio Workbench, Posit Connect, and Posit Package Manager, or comparable enterprise R and Python environments.
• Experience with Git version control, automated testing, CI/CD, logging, monitoring, and controlled software deployment.
• Strong understanding of clinical trial data and CDISC standards, including SDTM, ADaM, metadata-driven programming, and integrated data structures.
• Working knowledge of SAS and the ability to bridge established SAS workflows with modern R and Python solutions.
• Practical understanding of GenAI, LLMs, RAG, and AI-assisted programming in regulated environments, including their limitations and validation implications.
• Strong knowledge of GCP, ICH, 21 CFR part 11, data privacy, access control, audit trails, and validation expectations for clinical data systems.
• Demonstrates strong written and verbal communication skills, conveying complex technical concepts clearly to technical and non-technical stakeholders.
• Balances competing priorities and deadlines, ensuring timely and high-quality execution across multiple initiatives.
• Willing and able to travel domestically and internationally as needed.

Requirements

• 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.
• Owns the standardized cross-study and cross-compound clinical data model that harmonizes source structures, terminology, and variables into consistent, analysis-ready form.
• Develops automated incoming data quality and congruency checks, including completeness, structural conformance, visit and date consistency, cross-domain reconciliation, duplicates, and outliers.
• 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.
• Designs, develops, validates, deploys, and maintains interactive R/Shiny and Python dashboards for clinical data review and study health monitoring.
• Builds interactive patient profiles, data review listings, edit check outputs, coding review reports, and medical review applications.
• Develops reusable R and Python packages, modules, visualization components, and dashboard templates.
• Develops automated study team communications, including scheduled summaries of enrollment, safety events, data cleaning status, and other key study metrics.
• Partners with Data Management, Clinical Operations, Clinical Development, Safety, Biostatistics, and Statistical Programming to translate clinical review needs into reliable, intuitive dashboard functionality.
• Operationalizes R/Posit capabilities within Biometrics.
• Establishes R and Python development standards covering modular design, reusable code libraries, code review, automated testing, error handling, logging, and dependency management.
• Owns the lifecycle of pipelines, dashboards, and reusable components from requirements and prototyping through validation, production release, monitoring, enhancement, and retirement.
• Applies established validation, documentation, and quality standards to assigned pipelines and applications.
• Evaluates, prototypes, and implements AI and generative AI capabilities that measurably improve clinical data transformation, quality review, dashboard summarization, metadata and standards search, code generation and review assistance, or documentation drafting.
• Integrates approved LLM and retrieval augmented generation capabilities into R and Python applications.
• Applies human in the loop review, predefined acceptance criteria, traceability, and validation to AI-assisted outputs.
• Executes the clinical data integration, dashboard, and automation roadmap across assigned compounds.
• Leads technical and process improvement initiatives within assigned compounds and workstreams.
• Provides technical oversight of FSP, CRO, vendor, and consultant resources supporting assigned data integration and dashboard development work.
• Partners with study teams, Data Management, and Biostatistics at the study and compound level to gather requirements, resolve issues, and drive adoption of delivered tools.
• Provides training, mentoring, and technical guidance to statistical and clinical programmers on R/Posit, Python, data automation, dashboard development, and responsible AI practices.
• Monitors developments in R, Python, Posit, clinical data engineering, and AI use in drug development.

Benefits

• Competitive base, bonus, new hire and ongoing equity packages.
• Medical, dental, and vision insurance.
• Employer-paid life, disability, business travel and EAP coverage.
• 401(k) Plan with a fully vested company match 1:1 up to 5%.
• Employee Stock Purchase Plan with a 2-year purchase price lock-in.
• 15+ vacation days.
• 13 -15 paid holidays, including office closure between December 24th and January 1st.
• 10 days of paid sick time.
• Paid parental leave benefit.
• Tuition assistance.

Salary Range

$158,000 — $197,900 USD