Job Description

Zoetis is seeking a Senior Data Scientist to support global pharmacovigilance signal management supporting the team to translate complex safety information into clear, decision-ready insights for PV leadership and key stakeholders. This role will help strengthen routine safety monitoring, improve the consistency and usability of PV insights, and enable timely, high-quality communications aligned with business needs.

The role will also partner with internal digital/automation teams to expand analytics capabilities and improve how Zoetis synthesizes animal health data to better understand product performance in real-world use.

Duties and Responsibilities include but not limited to:

Advance signal detection and early alerting by leveraging new technologies to reduce false positives and strengthen trust in results through reproducible analysis approaches and controls. Standardize signal review outputs (evidence summaries, trend context, case-series characterizations) and ensure consistent governance across diverse data sources. Maintain end-to-end signal tracking and lifecycle documentation so conclusions, decisions, and actions remain transparent and traceable. Continuously improve PV data quality (completeness, consistency, de-duplication, coding, timeliness) and deliver “easy-to-digest” views (dashboards, scorecards, automated reports) to increase transparency into safety trends and data reliability. Enable leadership-ready insight delivery through a regular cadence of updates and ad hoc escalations, with summaries focused on what changed, why it matters, and what’s next; contribute to structured quarterly reviews for key products. Partner with PV leadership and digital/automation teams to evolve PV technology and signal management capabilities—translating needs into clear requirements and acceptance criteria, supporting testing and adoption (training, feedback loops), and ensuring continuity with minimal disruption.

Required / Strongly Preferred Skills:

• Python/R, SQL, and Git – these are essential baseline requirements
• Databases (relational required, graph databases nice to have)
• Statistical modeling (e.g. linear modeling, ANOVA, DoE) and machine learning (both supervised and unsupervised methods); deep learning nice to have
• GenAI / LLM experience, given the planned project directions, this should be explicitly listed as a requirement or at least a strong nice-to-have
• Text data wrangling and analysis
• Model deployment (understanding of dev, QA, and production environments)

Nice to Have:

• Power BI, given the existing PBI dashboard infrastructure already in place
• GitHub Copilot
• Application development / full-stack skills – since this will be the only dedicated resource for these projects, leaning toward a broader profile could be beneficial. That said, this capability could also be covered short-term through other Zoetis resources or an external contractor.

Educational Background:

• The current posting reads as though a candidate should hold degrees in both Life Sciences and Data Science. We recommend placing significantly more emphasis on the Data Science background, since the person will be working closely with the entire PV team of domain experts to ensure proper interpretation of the data.

Full time

Notice: Zoetis Recruiters will contact candidates via email from an address ending in @zoetis.com and may also initially connect with candidates through LinkedIn, including LinkedIn InMail. Zoetis does not use Gmail, Outlook, Yahoo, or other web-based/generic email domains to communicate about job opportunities, interviews, or offers of employment. If you receive a recruitment-related email message claiming to be from Zoetis that does not come from @zoetis.com, please treat it as suspicious. For your security, do not reply, click links, open attachments, share personal or financial information, or send money in response to unexpected or questionable recruitment communications.