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. Education (Recommended) MS, PhD in life sciences/DVM with 7+ years with applied data analytics and handling and interpretation of multimodal data MS or PhD in Data Science, Biostatistics, Epidemiology, Computer Science, or a related quantitative field with experience or training in veterinary/animal health, safety surveillance, or regulated life sciences. Required / strongly preferred - Senior-level experience delivering analytics in a quality-controlled environment (health, life sciences, regulated industry, or comparable). - Demonstrated success producing leadership-facing analytics deliverables (dashboards, recurring review materials, executive summaries). - Strong technical skills in Python and/or R, SQL, reproducible workflows (e.g., Git), and data visualization tools (e.g., Power BI/Tableau). Nice to have - Experience supporting enterprise system upgrades/migrations and analytics comparability/validation work. - Familiarity with pharmacovigilance concepts and signal management workflows. Full time Regular Colleague Any unsolicited resumes sent to Zoetis from a third party, such as an Agency recruiter, including unsolicited resumes sent to a Zoetis mailing address, fax machine or email address, directly to Zoetis employees, or to Zoetis resume database will be considered Zoetis property. Zoetis will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume. Zoetis will consider any candidate for whom an Agency has submitted an unsolicited resume to have been referred by the Agency free of any charges or fees. This includes any Agency that is an approved/engaged vendor but does not have the appropriate approvals to be engaged on a search. 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.

• Support global pharmacovigilance signal management • Translate complex safety information into clear insights for PV leadership • Advance signal detection and early alerting using new technologies • Standardize signal review outputs and ensure consistent governance • Maintain signal tracking and lifecycle documentation • Improve PV data quality and deliver transparent views to increase reliability • Enable leadership insight delivery through regular updates

Evaluate new data sources and modeling techniques while developing analytical tools and automations. Collaborate cross-functionally to enhance model monitoring and governance, enabling teams to independently access data and streamline decision-making...

Our mission at the Future Evidence Foundation is to dramatically improve lives by changing the way the world creates and uses knowledge. Covidence is our SAAS platform that enables health & science research teams to rapidly synthesise and uncover actionable insights from existing research in the world. We’re a well-funded not-for-profit and a world leader in our field. The Opportunity Covidence is seeking a senior level Data Scientist to join our team. You will be reporting to the CTO and be responsible for discovering, developing and deploying solutions to accelerate the systematic review workflow. As our third Data Scientist you will work within a cross functional team Product & Engineering team of 15 people. The team has already launched features that use external machine learning models e.g. to drive sort orders, to classify studies. We now want you to help us build and operationalise our own models. We’re early on this journey and have an initial implementation of extracting structured information from study documents, but we’re keen for you to help define the future roadmap and develop the next generation of AI and automation features for our users. The potential for Large Language Models (LLMs) and Natural Language Processing (NLP) to unlock scientific knowledge and make a difference in the world is huge. This role is a chance to use your skills to be part of that change. The ideal candidate will be a great communicator that has had recent hands-on experience building and deploying ML models that have solved user problems. You’ll get to: - Collaborate with the product and engineering team to identify areas for automation and improvement - Designing and developing state-of-the-art NLP algorithms, with a focus on orchestrating LLMs across various providers (OpenAI, Anthropic, Google, etc.) to optimize for cost, latency, and accuracy. - Analyse data and conduct experiments to improve the accuracy and efficiency of model - Build and deploy models that can be integrated into production applications - Evaluate emerging LLM tools and frameworks to maintain a competitive edge in research automation - Collaborate with leading ML practitioners in the research synthesis space to fundamentally change the way the world derives accurate insights from global research output What you bring: - Most importantly, we are looking for candidates who have worked closely with product and engineering teams. - Strong problem-solving skills with a data-driven mindset for complex research challenges. - Deep hands-on experience developing LLM solutions, including prompt engineering, fine-tuning, and multi-modal API integration from different providers. - Experience in LLM evaluation and benchmarking, specifically using robust and efficient frameworks to quantify model performance and factual consistency. - Strong programming skills in Python with experience in deploying ML/LLM models to production applications. - Experience with NLP techniques and tools for semantic analysis and information extraction. - Experience in building Retrieval Augmented Generation (RAG) pipelines using vector Databases (e.g. Milvus, Pinecone, or Chroma) and efficient retrieval strategies. - Experience with data visualization tools and common database technologies. - Bonus: - Expertise in building autonomous agentic loops using frameworks like LangGraph or CrewAI to handle multi-step reasoning tasks. - Experience in the use of data science to advance scientific research. - Knowledge of medical and/or scientific terminologies and ontologies. The Perks and Benefits: - Competitive salaries relevant to your experience level, reviewed twice yearly - Remote team so you can live and work in Australia or NZ, as long as you can offer at least a 4-hour workday crossover with the AEST time zone - Work week flexibility - Full time, part time or explore a flexible arrangement with us that best suits you and us - Gifted time off between Christmas and New Years - Support for parents with 14 weeks paid primary carers leave and 8 weeks paid leave for partners, available after only 6 months tenure - Access to wellbeing services & programs to support your wellbeing - A knowledge allowance and time so you keep learning and developing - Monthly home allowance to set up and run your home office. The Interview Process: If you are interested in this opportunity, please hit APPLY and send us through your details. We’ll be back in touch with you shortly. Should we proceed further you can expect 3 interviews: - Round 1: 20 min Zoom interview for us to get to know each other - Round 2: 60 min Zoom interview diving into your working style, experience and motivation - Round 3: 90 min Zoom interview where you’ll complete a practical exercise with some of our team members We don’t use AI in our screening process, please don’t use it in your application or interviews. If you are excited about the opportunity to shape the future of systematic reviews and have a track record of delivering innovative solutions, please apply. We look forward to hearing from you!