Consumer Data Scientist

Position Overview

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. You will work with one of the largest in-clinic and online pet parent behavior datasets in the world to design, build, and operationalize models and analytical frameworks that improve consumer acquisition, drive retention, influence product and brand preference, and enhance the consumer experience. You will partner closely with Marketing, Product, and Commercial leaders to transform ambiguous business questions into clear analytical challenges and actionable recommendations.

Key Responsibilities

• 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) for data-driven marketing and business decisions.
• Design and analyze experiments (A/B and multivariate tests) and apply causal inference methods to assess the impact of marketing, pricing, and product changes on consumer outcomes.
• Identify, scope, and prioritize high-impact data science opportunities that shape consumer experience, drive adoption, increase loyalty, influence brand preference, and deepen engagement.
• Establish scalable, efficient, and automated processes for large-scale data preparation, model training, scoring, and monitoring in collaboration with Data Engineering and Analytics teams.
• Translate complex analytical findings into clear, compelling stories and recommendations for non-technical stakeholders.
• Contribute to data science standards, best practices, documentation, and mentor team members in advanced analytics and modeling techniques.
• Collaborate across the organization to solve critical business challenges and support overall strategy.

Required Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative field is required. An advanced degree (Master’s or PhD) is 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 monitoring.
• Proven expertise in predictive modeling, machine learning techniques (e.g., regression, tree-based methods, clustering, time-series forecasting), SQL, and programming in Python and/or R.
• Experience designing data pipelines, automated analytical workflows, and reporting tools in collaboration with data engineering or BI teams.
• Excellent ability to interpret complex analysis into clear, concise business insights and strategic recommendations.

Benefits & Perks

• Compensation: $78,600 - $112,300 (Salary may vary based on skills, experience, and location)
• 401k savings & company match
• Paid time off and Paid holidays
• Maternity, Parental, Military leave and other leaves of absence
• Health, dental, and vision benefits with Health savings and Flexible spending accounts
• Life & disability benefits, Identity theft protection, and Pet insurance
• Eligibility for a short-term incentive plan for certain positions