Jobs at MSD Animal Health Technology Labs

Lead strategic forecasting for one or multiple therapy areas using statistical and strategic techniques (Monte Carlo, agent-based modeling, NLP, clustering). Drive forecast delivery, automation, and continuous improvement; collaborate with Finance, Research, Country teams and senior leadership; manage resources, select optimal forecasting methods, and communicate actionable insights to support decision making.

Lead global pharmaceutical asset forecasting using strategic and statistical methods. Drive forecasting innovation, automation, and stakeholder collaboration; manage team delivery, select optimal methods, and standardize models to improve forecast accuracy and decision-making across finance, manufacturing, development, and commercial functions.

Lead strategic pharmaceutical forecasting using advanced quantitative and qualitative methods. Deliver and automate long-range asset forecasts, drive methodological innovation, collaborate with cross-functional stakeholders, manage forecasting team and processes, and synthesize insights to inform finance, manufacturing, development and commercial decisions.

Serve as a DeltaV process control SME to upgrade and standardize systems, develop standards and SOPs, monitor and troubleshoot automation systems, integrate interfaces, ensure cybersecurity and compliance, and document technical guidance.

Lead design and deliver scalable end-to-end data platforms and pipelines using Spark, Python, SQL, Databricks, Airflow, and AWS. Architect lakehouse and dimensional models, drive CI/CD, mentor engineering teams, and ensure performance, security, and cost-efficiency across enterprise data solutions.

Lead design and implement end-to-end, scalable data platforms and Lakehouse architectures using Databricks, Spark, Python, SQL, Delta Lake and AWS. Build and optimize large-scale pipelines, orchestration with Airflow, CI/CD (GitHub Actions), Redshift modeling, and data modeling (star/snowflake). Mentor engineering teams, define data standards, and collaborate with stakeholders to deliver analytics and AI-driven data workflows.

Design, build, and maintain scalable ETL/ELT data pipelines using SQL, Python, and Spark. Orchestrate workflows with Apache Airflow and implement processing in Databricks (Delta Lake, notebooks). Leverage AWS services (S3, Glue, Redshift, EMR, Lambda) to ensure data quality, reliability, and performance. Collaborate with analytics and business teams, monitor production pipelines, and optimize performance. Exposure to agentic AI and AI-driven data workflows is desirable.

Design, build, and maintain scalable ETL/ELT data pipelines using SQL, Python, Spark, Airflow and Databricks on AWS. Ensure data quality and performance, optimize Redshift, collaborate with business and analytics teams, and monitor/ troubleshoot production workflows.

Design, build, and maintain scalable ETL/ELT data pipelines and workflows using Python, SQL, Spark, Airflow and Databricks on AWS. Ensure data quality and performance, optimize Redshift, collaborate with analytics and product teams, and monitor production pipelines.

Lead architecture and build scalable data platforms and Lakehouse solutions using Databricks, Spark, Python, SQL and AWS. Design ETL/ELT pipelines, orchestration with Airflow, data modeling (star/snowflake), CI/CD, and mentor data engineering teams to deliver reliable, high-performance analytics platforms.

Serve as primary operational lead for a cross-functional product team to manage incident, problem, and change processes. Drive monitoring, automation, release readiness, MTTR reduction, SLA/SLO adherence, and mentor support staff to improve production stability and operational maturity.