Job DescriptionThe Principal Data Scientist will serve as a strategic leader and technical expert driving enterprise-level transformation through the convergence of R&D data assets and the systematic integration of advanced AI/ML capabilities into organizational workflows. This role will work with cross-functional teams to define and architect scalable solutions that fundamentally transform how AbbVie leverages data and artificial intelligence to enhance strategic decision-making processes across the R&D pipeline and clinical development continuum.
• Acting as a key member of the R&D Convergence Core team, this position will identify systemic gaps in data convergence and workflow integration, then lead collaborative efforts to design and implement enterprise-wide solutions that create sustainable organizational capabilities rather than isolated point solutions. The Senior Principal Data Scientist will work at the intersection of scientific strategy, advanced analytics, and organizational transformation to establish integrated frameworks that enable scalable AI/ML adoption across therapeutic areas and functional domains.
• This role requires demonstrated expertise in translating cutting-edge AI technologies -including advanced machine learning, deep learning, and generative AI - into production-ready workflow integrations that drive measurable improvements in R&D innovation and efficiency, clinical trial optimization, and strategic portfolio decision-making processes. The position demands a proven track record of leading enterprise-scale data and AI initiatives that achieve cross-functional adoption and deliver sustained organizational impact
Responsibilities:Enterprise Strategy & Workflow Transformation - Lead the identification and assessment of enterprise-level gaps in data convergence, analytical capabilities, and AI/ML integration across R&D workflows; design comprehensive strategies to address systemic challenges through scalable, integrated solutions
- Architect and champion collaborative cross-functional frameworks that enable the systematic integration of advanced AI/ML capabilities into existing R&D and clinical workflows, ensuring solutions are extensible, maintainable, and aligned with enterprise data strategies.
- Drive organizational transformation initiatives that fundamentally enhance how data and AI inform strategic decision-making across the R&D portfolio, therapeutic development, and clinical trial execution
- Establish and evangelize best practices, standards, and governance frameworks for enterprise-wide AI/ML workflow integration that ensure consistency, quality, and regulatory compliance
Advanced AI/ML Solution Architecture - Oversee the development of sophisticated, production-grade AI/ML workflow orchestrations that integrate multiple data sources, analytical techniques, and decision support capabilities into cohesive enterprise solutions
- Lead the collaborative application of state-of-the-art AI technologies including advanced machine learning, deep learning architectures, natural language processing, and generative AI to transform complex R&D and clinical development processes
- Architect end-to-end analytical pipelines that seamlessly connect data ingestion, feature engineering, model training, deployment, monitoring, and continuous improvement within enterprise platforms.
- Drive innovation in workflow automation and intelligent process optimization, leveraging AI/ML to reduce cycle times, enhance quality, and improve decision accuracy across the R&D continuum
Cross-Functional Leadership & Collaboration - Serve as the technical leader for high-impact, cross-functional initiatives requiring advanced data convergence and AI/ML integration across multiple therapeutic areas and R&D functions
- Partner with senior leadership across R&D, IT, Data Science, and business functions to align workflow transformation initiatives with strategic priorities and ensure executive-level buy-in
- Represent R&D in enterprise-wide forums and decision-making bodies related to data strategy, AI governance, and technology architecture, advocating for solutions that balance innovation with scalability and compliance
Organizational Capability Building - Oversee development of reusable, modular AI/ML components and workflow templates that can be rapidly adapted across different therapeutic areas and functional domains
- Collaborate with Data Engineering, MLOps, and IT teams to establish robust infrastructure and platforms that support the scalable deployment and operation of integrated AI/ML workflows
- Establish metrics and monitoring frameworks to continuously assess the impact of AI/ML workflow integrations on R&D efficiency, decision quality, and strategic outcomes
Technical Excellence & Innovation - Maintain deep expertise in the latest advances in artificial intelligence, machine learning, and analytical methodologies; evaluate emerging technologies for their potential to drive enterprise-wide workflow transformation
- Ensure all AI/ML solutions adhere to regulatory requirements, data governance policies, ethical AI principles, and AbbVie quality standards
- Design solutions with security, privacy, auditability, and explainability considerations embedded from inception, particularly for regulated clinical and healthcare applications
- Translate complex technical architectures and AI/ML methodologies into clear strategic narratives for diverse stakeholders, from technical teams to executive leadership
Qualifications- PhD in Computer Science, Statistics, Bioinformatics, Computational Biology, Applied Mathematics, Data Science, or related quantitative field strongly preferred; Master's degree with exceptional demonstrated expertise and extensive experience considered
- 4-5+ years of progressive experience building, deploying, and scaling advanced AI/ML solutions in enterprise environments, with demonstrated leadership of large-scale, cross-functional data and analytics initiatives.
- Proven track record of leading enterprise-wide workflow projects that resulted in measurable organizational impact and sustainable capability development
- Minimum 5+ years of experience working in highly matrixed, complex organizational environments (Preferred experience in Consulting across pharmaceutical, biotech, healthcare, or similarly regulated industries strongly preferred)
Technical Expertise - Expert-level proficiency in advanced machine learning and artificial intelligence, including deep learning, neural network architectures, ensemble methods, transfer learning, and generative AI technologies
- Demonstrated mastery of ML/AI frameworks and platforms (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face) and their application to complex, real-world problems
- Advanced programming capabilities in Python and R, with strong software engineering principles; experience with production code development, version control, CI/CD pipelines, and testing frameworks
- Deep understanding of MLOps principles, model lifecycle management, workflow orchestration tools (e.g., Airflow, Kubeflow, MLflow), and enterprise deployment architectures
- Experience with cloud computing platforms (AWS, Azure, others) and distributed computing frameworks for large-scale data processing and model training
- Strong expertise in data architecture, data integration patterns, and modern data platforms supporting enterprise analytics
Strategic & Leadership Capabilities - Demonstrated success leading enterprise-scale initiatives that transform organizational workflows and decision-making processes through data and AI integration
- Proven ability to influence senior leadership, build cross-functional coalitions, and drive adoption of complex technical solutions across large, matrixed organizations
- Strong change management acumen and experience driving organizational transformation in regulated environments
- Track record of successful collaboration with multidisciplinary teams including data scientists, software engineers, clinicians, scientists, and business stakeholders
Domain Knowledge - Experience in pharmaceutical R&D, clinical development, or healthcare analytics strongly preferred
- Understanding of regulatory requirements, clinical trial design, drug development lifecycle, and healthcare data governance preferred
- Working knowledge of healthcare data standards (e.g., CDISC, OMOP) and FAIR data frameworks preferred
Additional InformationApplicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of thisposting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location,and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission,incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless anduntil paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law.
