Associate Director, Data Science & AI Solutions

Job Description

The mission of the Analytics & Technology Systems QA group is to provide the foundation to identify, explore, and efficiently develop solutions to enhance our quality oversight activities.

Under the direction of the Senior Director, Analytics & Technology Systems of our Research & Development Division QA, we are seeking an Associate Director, Data Science & AI Solutions, to join our R&D Quality Assurance Analytics & Tech Systems team. In this role, you will bridge the gap between hands-on advanced software development and strategic business partnership. You will lead the design, deployment, and long-term lifecycle of our next-generation AI and data science solutions—ranging from traditional machine learning and simulations to custom generative AI applications (such as RAG and agentic workflows).

As a technical and strategic leader, you will collaborate with business stakeholders to identify high-value opportunities, translate complex technical concepts for different audiences, and partner with governance bodies to ensure all advanced analytics tools are robust, compliant, and scalable.

Key Responsibilities

1. AI Development & System Lifecycle

• Technical Delivery: Build, deploy, and maintain advanced AI applications (including custom RAG pipelines and agentic systems) alongside traditional analytics solutions (forecasts, simulations, and optimizations) to solve critical research & development quality business challenges.
• Environment Management: Work within enterprise analytics platforms (e.g., Dataiku, Posit Workbench) to monitor, enhance, and scale existing operational analytics systems.

2. GxP AI Governance & Compliance

• Regulatory Alignment: Collaborate with the GxP AI Governance Program to develop frameworks that ensure AI solutions adhere to regulatory requirements, validation playbooks, and standardized monitoring protocols.

3. Business Partnership & Technical Translation

• Translational Communication: Act as the primary technical translator, explaining complex AI algorithms, models, and limitations to non-technical stakeholders and leadership in a clear, business-friendly manner.
• Demand Intake: Collaborate with business leaders to identify operational challenges and propose high-value data science and AI use cases.
• Business Acumen: Demonstrates a strong willingness to learn and understand business processes, priorities, and stakeholder’s needs to drive meaningful outcomes.

4. Leadership & Upskilling

• Team Mentorship: Educate and upskill QA team members on modern tech stacks, Large Language Models (LLMs), and general data literacy.
• External Representation: Represent our company in cross-functional forums, such as IMPALA (Intercompany Quality Analytics).

Required Qualifications

• Educations/Experience:  BS/BA degree in relevant area and 5+ years of experience in the pharmaceutical, biotech or technology related industry.
• Analytical & Programming Core: Minimum 5 years of professional experience using Python, R, and advanced SQL to design and deploy machine learning, forecasting, or optimization models.
• Modern AI Engineering: Hands-on experience developing custom RAG architectures, working with LLM APIs, and utilizing core MLOps practices (version control/Git, monitoring, and model maintenance).
• Data Engineering & Visualization: Proficiency in designing user-friendly dashboards (PowerBI or Spotfire) and a foundational understanding of Extract, Transform, Load (ETL) pipelines and data structures.
• Cloud & Architecture: Familiarity with hosting and deploying AI solutions or agentic pipelines in cloud environments (AWS, Azure, or GCP).
• Regulated Industry Experience: Prior experience in a regulated pharmaceutical (GxP) environment, with exposure to software validation or AI governance frameworks.
• Communication & Influence: Exceptional communication skills with a proven ability to distill complex technical terminology into actionable insights for non-technical business partners.
• Global Collaboration: Experience working with and supporting different, cross-functional teams in a global, matrixed organization.
• Passionate Learner: Continuously explores emerging technologies, including generative AI, and identifies opportunities to apply them to drive innovation and business value.

Required Skills:

AI Programming, Audience View, Biopharmaceutical Industry, …