Consumer Data Scientist

Job Description Consumer Data Scientist

United States – Remote

Covetrus is looking for a Consumer Data Scientist to drive and support advanced analytics and applied data science that accelerates Covetrus ’ consumer-facing marketing, product experiences, and strategic business initiatives. As part of Covetrus , you will work with one of the largest in-clinic and online pet parent behavior datasets in the world . You will design, build, and operationalize models and analytical frameworks that improve new consumer acquisition, drive retention, influence product and brand preference, and enhance the experienc e of our consumer-facing products.

You will partner closely with Marketing, Product, and Commercial leaders to translate ambiguous business questions into clear analytical problems, develop data-driven solutions, and communicate recommendations that shape strategy. You will contribute to a culture of collaboration, innovation, and continuous improvement as you provide insight into the business and drivers of consumer behavior, loyalty, and product preferences.

• Drive and support the development, validation, and deployment of predictive and machine learning models (e.g., propensity, churn, LTV, recommendations, next best action, marketing response) that support data-driven marketing and business decisions for the Prescription Management and other consumer businesses.

• Design and analyze experiments (A/B and multivariate tests) and apply causal inference methods to measure the impact of marketing, pricing, and product changes on key consumer outcomes.

• Identify, scope, and prioritize high-impact data science opportunities that shape consumer experience, drive adoption, increase loyalty, influence brand preference, and deepen consumer engagement.

• Maintain a deep understanding of consumer behavior, competitive trends, and business drivers; proactively surface insights and hypotheses that inform strategy and roadmap decisions.

• Analyze key trends and build robust statistical and machine learning models to predict consumer behavior using strong statistical rigor and best practices.

• Establish scalable, efficient, and automated processes for large-scale data preparation, model training, scoring, and monitoring in partnership with Data Engineering and Analytics teams.

• Partner with teams across the prescription management and broader consumer business to design, develop, and maintain forecasts, analytical tools, and dashboards that highlight key business drivers and model outputs.

• Translate complex analytical findings into clear, compelling stories and recommendations tailored to non-technical stakeholders, driving alignment and action.

• Contribute to data science standards, best practices, and documentation, and mentor team members in advanced analytics and modeling techniques.

• Collaborate across the organization to solve critical business challenges and support overall business strategy.

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative field required.

• Advanced degree (Master’s or PhD) in a quantitative discipline a plus.

• 3+ years of experience in applied data science, machine learning, or advanced analytics in a consumer, digital, or eCommerce environment.

• Demonstrated experience supporting end-to-end modeling projects—from problem framing and data preparation through model development, validation, deployment, and performance monitoring.

• Proven experience in predictive modeling and machine learning, including techniques such as regression, regularization, tree-based methods (e.g., random forest, gradient boosting), classification, clustering/segmentation, time-series forecasting, and/or uplift modeling.

• Proficiency in SQL and working with large-scale, complex datasets in modern data warehouses; experience with Snowflake is preferred.

• Strong programming skills in Python and/or R for data science.

• Experience designing and building data pipelines or automated analytical workflows and reporting tools in partnership with data engineering or BI…