Über diese Associate Director, Clinical Data Integration & AI Programming Stelle bei Acadia Pharmaceuticals Inc.
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, validates, deploys, and maintains interactive R/Shiny and Python dashboards for clinical data review and study health monitoring, covering enrollment, adverse and serious adverse events, efficacy data review, laboratory trends, protocol deviations, visit compliance, data cleaning status, and operational metrics
- Builds interactive patient profiles, data review listings, edit check outputs, coding review reports, and medical review applications, transitioning these deliverables from manual or SAS-based workflows into reproducible R/Posit solutions
- Develops reusable R and Python packages, modules, visualization components, and dashboard templates, together with common metric definitions and navigation patterns, so outputs are consistent and comparable across studies and compounds
- 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 and drives adoption through training and documentation
Engineering Standards, Validation, and Platform
- Operationalizes R/Posit capabilities within Biometrics, including Posit Workbench, Posit Connect, Package Manager, controlled package environments, application publishing, access management, and governed deployment
- Establishes R and Python development standards covering modular design, reusable code libraries, code review, automated testing, error handling, logging, and dependency management, and applies Git version control and CI/CD practices to pipelines and applications
- Owns the lifecycle of pipelines, dashboards, and reusable components from requirements and prototyping through validation, production release, monitoring, enhancement, and retirement, with documentation, traceability, and change control appropriate to a regulated environment
- Applies established validation, documentation, and quality standards to assigned pipelines and applications, and supports audits and inspections as subject matter expert for the solutions the incumbent has built
Applied AI Capabilities
- 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 where they deliver clear operational benefit and can be appropriately governed, including natural language querying of approved internal standards, specifications, and study documentation
- Applies human in the loop review, predefined acceptance criteria, traceability, and validation to AI-assisted outputs, and determines when AI-assisted methods are appropriate versus when deterministic, validated programming is required
Operational Leadership and Collaboration
- Executes the clinical data integration, dashboard, and automation roadmap across assigned compounds, and prioritizes work within an agreed backlog
- Leads technical and process improvement initiatives within assigned compounds and workstreams, and recommends sourcing approaches and tooling for consideration by functional leadership
- Provides technical oversight of FSP, CRO, vendor, and consultant resources supporting assigned data integration and dashboard development work, including specification, review, and acceptance of their deliverables
- 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, and recommends relevant advances for adoption
- Other responsibilities as assigned.
Education/Experience/Skills
- Bachelor’s degree in statistics, biostatistics, computer science, data science, biomedical informatics or a related science field. An equivalent combination of relevant education and experience may be considered
- 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. Demonstrated experience delivering technical solutions that span multiple studies is required
- 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 ability to travel domestically and internationally as needed
Physical Requirements
This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds. This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.
#LI-REMOTE #LI-RE1
In addition to a competitive base salary, this position is also eligible for discretionary bonus and equity awards based on factors such as individual and organizational performance. Actual amounts will vary depending on experience, performance, and location.
What we offer US-based Employees:
- 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
EEO Statement (US-based Employees): Studies have shown that women and people of color are less likely to apply for jobs unless they believe they meet every one of the qualifications in the exact way they are described in job postings. We are committed to building a diverse, equitable, inclusive, and innovative company, and we are looking for the BEST candidate for the job. That candidate may be one who comes from a less traditional background or may meet the qualifications in a different way. We strongly encourage you to apply, especially if the reason you are the best candidate isn’t exactly what we describe here.
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