Senior Data Scientist, Environmental, Health & Safety; EHS

Position: Senior Data Scientist, Environmental, Health & Safety (EHS)
Company Description

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on Linked In, ()  Facebook, Instagram () , X ()  and You Tube.

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Job Description

The Senior Data Scientist will lead the strategy, design, and implementation of agentic and generative AI capabilities that advance the Global Environmental, Health & Safety (GEHS) organization's ability to anticipate risk, improve decision quality, strengthen compliance, and scale operational excellence. This role is accountable for translating complex EHS business needs into production-ready AI solutions, including intelligent agents, retrieval-augmented generation based tools, predictive analytics, natural language processing, and responsible AI frameworks.

The candidate will partner closely with Global EHS, Business Technology Solutions (BTS), internal data science organization, data engineering, governance, and business stakeholders to build scalable, secure, explainable, and sustainable AI-enabled solutions that improve how EHS professionals access knowledge, assess risk, automate workflows, and make data-driven decisions across the enterprise.

Responsibilities List up to 10 main responsibilities for the job. Include information about the accountability and scope.

+ Lead the development and execution of the Global EHS agentic and generative AI strategy, including prioritization of high-value use cases, solution roadmaps, implementation plans, and measurable business outcomes;

+ Design, build, evaluate, and scale AI-enabled solutions such as intelligent agents, retrieval-augmented generation workflows, semantic search, knowledge assistants, predictive risk models, and workflow automation tools that improve EHS decision-making and operational agility;

+ Partner with Global EHS, BTS, data engineering, governance, legal, privacy, cybersecurity, and business stakeholders to ensure AI solutions are secure, compliant, explainable, auditable, and aligned with enterprise technology standards and responsible AI expectations;

+ Translate complex EHS business challenges into data science and AI product requirements, including problem framing, data readiness assessment, model selection, solution architecture, evaluation criteria, implementation approach, and sustainment model;

+ Establish reusable AI patterns, prompt and evaluation libraries, data pipelines, model monitoring practices, and implementation playbooks to accelerate safe and consistent adoption of AI across EHS programs and sites;

+ Develop and execute advanced analytics and machine learning approaches to identify emerging compliance, injury and illness, operational, and sustainability risks using structured and unstructured EHS data sources;

+ Communicate AI strategy, solution performance, risks, limitations, and business value to technical and non-technical audiences, including senior leaders, functional stakeholders, and end users;

+ Provide technical leadership and coaching to internal partners, external vendors, and technical contributors to ensure high-quality delivery, adoption, and continuous improvement of AI-enabled EHS solutions;

+ Drive the improvement of EHS data infrastructure, , metadata, data quality, and governance practices needed to support trusted AI, analytics, and automation at enterprise scale; and

+ Maintain awareness of emerging AI capabilities, regulatory expectations, and EHS risk trends, and determine how they can be responsibly applied to improve EHS performance, compliance, and business outcomes.

Qualifications

+ Bachelor's Degree with 7 years' experience;
Master's Degree with 6 years' experience' PhD with 2 years' experience. Background in life sciences or work experience in the pharmaceutical industry preferred.

+ Possess thorough theoretical and practical…