Senior Scientist, Computational Safety

Description We are seeking a Senior Scientist, Computational Safety to develop and apply advanced AI/ML and agentic AI workflows for predictive toxicity and liability assessment. This role integrates diverse toxicological and biological data to support data driven liability assessment across drug discovery and development. The Senior Scientist will play a key role in curating and consolidating diverse tox and biological data (e.g., omics, genetics, literature, RWD, competitive intelligence) for agentic AI model development for next generation target liability assessment and prediction toxicology efforts. Working closely with toxicologists, discovery scientists, clinical safety, bioinformatics, data science, and IT partners, this position will translate complex computational insights into clear, actionable recommendations that improve pipeline quality and reduce late‑stage attrition. As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunities for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees. Duties & Responsibilities

• Lead the development, implementation, and application of advanced AI/ML models, including agentic AI workflows, to support predictive toxicity and safety liability assessment for projects and portfolios.
• Design and execute integrative computational strategies that combine multi‑modal toxicological and biological data (e.g., omics, genetics, literature, RWD, competitive intelligence) to generate robust, interpretable safety insights.
• Support computational safety risk assessment by providing early, data‑driven evaluations of potential toxicological liabilities to inform target selection, and program advancement decisions.
• Collaborate closely and effectively communicate with Toxicology, Discovery, Bioinformatics, Data Science, and IT teams to ensure alignment of computational approaches with biological context, technical infrastructure, and project needs. Requirements
• Master's degree with 6 + years of relevant experience or Ph.D. with 1-3 years of applicable industry or post‑doctoral experience in Computational Toxicology, Computational Biology, Bioinformatics, Molecular Biology
• At least 2 years in safety risk assessment
• Expertise in multi omics and toxicogenomic, data integration, and predictive safety assessment
• Familiarity with major large language models (LLMs), with hands‑on experience in Unix‑based systems and cloud computing environments
• Experience applying AI driven reasoning model to integrate multi omics, literature, and safety data
• Strong communication skills with the ability to translate complex AI and computational outputs into actionable insights
• Proven ability to collaborate effectively across toxicology, discovery, data science, and IT teams Eligibility Requirements
• Must be legally authorized to work in the United States without restriction.
• Must be willing to take a drug test and post-offer physical (if required)
• Must be 18 years of age or older @computationalinnovation Compensation Data This position offers a base salary typically between $140,000 and $222,000.

The position may be eligible for a role specific variable or performance-based bonus and or other compensation elements. For an overview of our benefits please click here. (https://www.boehringer-ingelheim.com/us/careers/benefits-rewards) All qualified applicants will receive consideration for employment without regard to a person's actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.