Overview Are you passionate about applying cutting-edge AI/ML to transform drug discovery? The Pharmacokinetics, Dynamics, Metabolism, and Bioanalytics (PDMB) department of our company Research Laboratories is seeking an AI/ML expert to help reimagine how PDMB assesses and optimizes drug candidates. You will join a dynamic Data Science team accelerating discovery through advanced analytics, predictive modeling, and decision-support tools. In this role, you will invent, build, and deploy novel AI/ML approaches to identify and optimize drug candidates with balanced efficacy, safety, and developability profiles. You’ll collaborate closely with principal investigators and lab-based scientists to refine experimental designs, generate testable hypotheses, and deliver intuitive visualizations and models at the intersection of translational PK/PD, ADME, bioanalytics, and data science. In this role, you will: Develop and deploy AI/ML models (e.g., active learning, Bayesian optimization, multi-objective optimization) to improve decision-making in preclinical and early development. Build robust data pipelines to capture, integrate, curate, and visualize multimodal data (in vitro, in vivo, in silico; PK/PD, ADME, omics, imaging) to enable reproducible analysis at scale. Partner with IT data engineers/architects to design scalable, secure data and model infrastructure (data lakes, feature stores, MLOps) aligned with PDMB scientific needs. Inform project strategy by guiding experimental design, assay selection, and candidate optimization; communicate model insights, uncertainty, and trade-offs to cross-functional teams. Translate complex analytics into actionable recommendations and easy-to-use tools/dashboards for scientists and project leaders. Stay current on emerging methods (e.g., foundation models, generative design, causal inference) and evaluate their applicability to PDMB problems. Note: This position is available in SSF, CA; Boston/Cambridge, MA; Rahway, NJ or West Point, PA based on candidate preference. Qualifications Education: Ph.D. (or Ph.D. candidate with expected graduation date by March 31, 2026) in Computer Science, Statistics, Applied Mathematics, Bioinformatics, Computational Biology, Computational Chemistry, Chemical Informatics, Engineering or related fields with relevant experience. Required Experience and Skills: Proven track record of research with first-coauthor publications at top-notch peer-reviewed journals or conferences Strong foundation in statistics and machine learning, including model development, validation, and performance/uncertainty assessment. Experience working with high-dimensional, heterogeneous datasets; grounding in data quality, curation, and feature engineering. Ability to communicate complex analyses clearly to non-experts and to collaborate effectively in interdisciplinary teams. Preferred Experience and Skills: Domain knowledge in chemistry, molecular biology, and/or biochemistry; familiarity with PK/PD and ADME concepts. Experience with deep learning or generative models for molecular design, QSAR, property prediction, or LLM on scientific text. Experience with cloud platforms and data/ML services (AWS/Azure/GCP), containers (Docker), workflow orchestration (Airflow, Prefect), and MLOps (MLflow, SageMaker). Ability to influence and enable scientific teams to adopt data-driven methods and positive change. US and Puerto Rico Residents Only: Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please consider accommodations during the application or hiring process. We are an Equal Employment Opportunity Employer and provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other legally protected characteristics. For more information about personal rights under U.S. Equal Opportunity Employment laws, visit the EEOC Know Your Rights and related resources. U.S. Hybrid Work Model Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid model consisting of three on-site days per week, with Friday remote, unless business-critical tasks require on-site presence. This model does not apply to field-based positions or roles designated as remote, or where otherwise restricted by an agreement. The salary range for this role is $156,500.00 - $246,300.00. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable. We offer a comprehensive package of benefits, including medical, dental, vision, retirement benefits (401(k)), paid holidays, vacation, and sick days. More information about benefits is available in our compensation and benefits materials. You can apply for this role through the company careers site. The application deadline for this position is stated on this posting. San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with local ordinances. Los Angeles Residents Only: We will consider all qualified applicants, including those with criminal histories, in a manner consistent with applicable laws. Search Firm Representatives: Merck & Co. does not accept unsolicited assistance from search firms for employment opportunities. No fee will be paid in the absence of a valid written agreement. Employee Status: Regular Relocation: Domestic/International VISA Sponsorship: Yes Travel Requirements: 10% Flexible Work Arrangements: Hybrid Shift: 1st - Day Required Skills: ADME, AI, Biochemistry, Chemistry, Data Analysis, Datasets, Deep Learning, High Dimensional Data, Machine Learning, PKPD Modeling, Statistics Preferred Skills: Molecular Biology, PKPD, Data Science Collaboration, Cloud/MLOps familiarity

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