Zoetis is looking to analyze complex data sets to deliver actionable insights that drive strategic business decisions, specifically in marketing and campaign targeting, to maximize ROI and optimize future strategies.
Requirements
- Expert in Python and PySpark; strong SQL skills; experience with Databricks.
- Practical experience with Gen AI frameworks, tools, and large language models for data analysis and personalization.
- Proficient with Git for collaborative code development and management.
- Experience building and maintaining data pipelines; knowledge of cloud data platforms.
- Skilled in predictive modeling, segmentation, time series analysis, and Gen AI/LLM applications.
- Experience with code versioning, testing, and deployment.
Responsibilities
- Design, extract, and refine campaign lists using advanced data science and Gen AI techniques.
- Analyze campaign performance and outcomes, delivering actionable recommendations to maximize ROI and optimize future targeting strategies.
- Develop and implement predictive models, segmentation, and time series analyses to support marketing strategies.
- Apply Gen AI frameworks and large language models to drive personalization and campaign effectiveness.
- Continuously monitor and refine models to ensure accuracy, relevance, and business impact.
- Utilize Python, PySpark, Databricks, Gen AI frameworks, and SQL for data processing, analysis, and modeling.
- Collaborate with data engineering teams to ensure robust, scalable data pipelines and infrastructure.
Other
- Advanced degree in Data Science, Computer Science, Engineering, or a related discipline.
- 4+ years’ experience in analytics, data science, or decision support, ideally in commercial or marketing environments.
- Proven ability to collaborate with business stakeholders to deliver actionable insights and drive measurable results.
- Hands-on experience with campaign analytics, predictive modeling, Gen AI/LLMs, and stakeholder engagement.
- Exceptional interpersonal, written, and verbal communication skills.
