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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI and Data Science Lead - **Company:** AbbVie Inc. - **Location:** Florham Park, NJ, United States - **Experience:** Expert - **Salary:** $141,500.0 - $268,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computing Platforms, Big Data, Cloud Computing, Information Engineering, Data Governance, R (Programming Language), Python (Programming Language), Machine Learning, Azure Machine Learning, Tableau (Software), Apache Spark, Deep Learning, Model Validation, Data Lineage, Data Analytics, Data Management, Machine Learning Operations, Dataiku, Data Pipelines, GXP - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=dd8852ef692b04d2 ## About the Role * Bachelor's Degree with 9 years' experience; Master's Degree with 8 years' experience; PhD with 4 years' experience. * Significant experience leading multi-disciplinary teams delivering enterprise-scale data science platforms and applications, preferably in regulated industries such as pharmaceuticals, life sciences, or healthcare operations. * Deep expertise in data science methods (ML, AI, statistics), modern data engineering (cloud, big data, pipeline orchestration), and business analytics, with mastery of tools such as Python, R, Dataiku, AWS SageMaker, Spark, Tableau, etc. * Demonstrated ability to define and execute governance frameworks for data quality, master data, model lifecycle management, and regulatory compliance. * Extensive consulting and stakeholder management experience, including effective communication of complex technical solutions to executive audiences and cross-functional business partners. * Proven ability to drive innovation (strategy, whitepapers, roadmaps), develop cross-functional partnerships, and lead technology transfer initiatives to embed analytics into core business processes. * Experience mentoring and growing diverse teams, with a focus on inclusion, equity, and continuous learning. * Self-driven, highly adaptable, and able to quickly master new domains and tools in response to emerging business or technology trends. Preferred: * Experience delivering data science solutions in industry (non-academic settings strongly preferred), with demonstrated progression in leadership roles. * Experience with data-driven transformation in Quality, Supply Chain, Procurement, or Central Operations within a large pharmaceutical or life sciences organization, and deep understanding of GxP practices. * Background in technology innovation, MLOps, platform architecture, or boutique/strategy consulting with measurable stakeholder impact. ## Description As Data Science and AI Lead overseeing Platform, Governance, and Delivery for Data Science and AI solutions at AbbVie, you will lead a diverse team of data scientists responsible for designing, executing, and scaling data science solutions across the enterprise. Reporting into Operations Business Insights (OBI), you will establish and execute the vision and roadmap for a robust, agile, and compliant data science platform, ensuring strong governance practices and operational excellence in delivering impactful data science to drive innovation, performance, and agility company wide. Leading a multifaceted team, you will have end-to-end accountability for platform strategy, stakeholder engagement, project delivery, and talent development. You will be expected to set the standard for technical and consulting excellence, foster a culture of continuous learning, and promote effective collaboration within and outside your group, including functional data scientists, business partners, academic collaborators, and technology leaders., * Provide leadership in developing, maintaining, and governing the data science platform to enable secure, scalable, and compliant analytics throughout AbbVie's global operations, spanning Supply Chain, Quality, Procurement, Manufacturing, and Science & Technology. * Oversee the delivery lifecycle from requirements discovery, solution design, and modeling through deployment and monitoring of productionized data science applications, studies, and proofs of concept by leading teams of diverse data scientists and analysts. * Lead and champion best practices in data governance, stewardship, and quality, ensuring compliance with regulatory and organizational standards (e.g., GxP, master data management, data lineage, model validation, etc.). * Push forward with semantic engineering and agentic engineering, best practices and capability delivery to support more advanced AI use cases. Oversee architects involved in semantic and agentic engineering and solutioning. * Develop and promote advanced analytics capability, including supervised/unsupervised machine learning, deep learning, AI/ML platform services, and the enablement of novel AI applications such as RAG and semantic layering for human-in-the-loop systems. * Foster strategic partnerships with senior functional leaders, technology stakeholders, and external collaborators to accelerate the transfer of advanced methods into high-value business solutions. * Collaborate on group strategy and roadmap, enable cross-functional GenAI initiatives, and serve as a thought leader for education, awareness, and innovation in enterprise data science. * Ensure robust consulting, communication, and change management plans are in place to drive adoption of data science solutions at all organizational levels, including executive leadership. * Mentor, coach, and develop a diverse team, building a pipeline of talent that can take on increasingly complex projects and lead education initiatives (journal clubs, technical upskilling, peer review, etc.). ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)