The Data Scientist is a key member of the Pricing Strategy & Insights team, responsible for leveraging advanced analytics, predictive modeling, machine learning, and statistical methodologies to support pricing strategy, revenue optimization, and enterprise decision-making across VCA and Mars Veterinary Health. This role focuses on leveraging large, complex datasets to uncover patterns in pricing, utilization, and client behavior, and to design analytical models and optimization approaches that improve pricing decisions, revenue outcomes, and long-term strategic planning.

Operating at the intersection of data science, pricing strategy, and business decision-making, the Data Scientist translates analytical questions into robust statistical and machine-learning models (e.g., price elasticity, demand forecasting, and segmentation) and translates model outputs into clear, actionable insights for pricing leaders and cross-functional stakeholders. This role also supports a test-and-learn culture by applying experimental and measurement approaches (e.g., A/B testing) to quantify the impact of pricing actions and promotional strategies.

In addition to hands-on model development, the Data Scientist is responsible for validating analytical approaches, documenting assumptions and limitations, and partnering with analysts and technical teams (e.g., data engineering) to enable scalable data pipelines and production-ready model deployment into dashboards and decision tools. Reporting to the Director, Pricing Strategy & Insights, this role helps elevate the analytical maturity of the Pricing organization by introducing repeatable modeling techniques, best practices, and forward-looking insights that strengthen how pricing decisions are evaluated, governed, and executed.

This role requires associates to work a hybrid schedule out of one of the MVH North America Hub Locations - Los Angeles, CA.

Essential Responsibility/Tasks:

• Advanced Analytics & Modeling: Design, build, and maintain statistical and machine-learning models to support pricing decisions, including price elasticity, demand forecasting, segmentation, and drivers of utilization and spend.
• Pricing Optimization & Decision Support: Develop analytical approaches and (as appropriate) optimization methods that account for profitability and business constraints; translate model outputs into practical pricing recommendations and scenario implications for leaders.
• Experimentation & Impact Measurement: Design and analyze statistical experiments (e.g., A/B tests) to evaluate pricing and promotional effectiveness; ensure results are clearly communicated and inform future pricing actions.
• Data Engineering Partnership & Data Preparation: Prepare and transform large-scale datasets using SQL and Python/R; partner with data engineering and analytics teams to ensure data quality, consistent definitions, and scalable pipelines.
• Model Validation, Documentation & Governance Enablement: Validate models for accuracy and stability; document methodologies, assumptions, and limitations; support responsible use of analytics in governance and decision forums.
• Deployment & Enablement: Support operationalization of models into dashboards, tools, and recurring decision processes (including monitoring and refresh); train/enable analyst partners on model interpretation and usage.
• Other Related Duties as Assigned: Support ad hoc analyses, leadership requests, and cross-functional initiatives related to pricing, promotions, or growth strategy.

EDUCATION/EXPERIENCE:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Operations Research, or related field. Master's degree or PhD in related field is preferred.
• 5+ years of experience in data science, advanced analytics, or statistical modeling
• Experience in pricing, revenue optimization, demand forecasting, or commercial analytics is preferred.

*All degrees will be deemed "or equivalent combination of education and experience" unless absolutely required to do the job (i.e., DVM degree for Veterinarian, Law degree for Attorney, etc.).

PREFERRED SKILLS AND QUALIFICATIONS:

• Python (preferred libraries: scikit-learn, XGBoost, pandas, NumPy, matplotlib)
• SQL (large-scale structured datasets)
• Statistical modeling, machine learning, and optimization techniques
• Data visualization tools (Power BI/Tableau or equivalent) and executive presentations
• Advanced Microsoft Excel (modelling and communication)

Additional Information: Compensation is negotiable based on education, experience, and other relevant credentials. The US base salary range for this full-time position is $107,656 - $161,485. Our salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only.

If you are a current associate, you need to apply through our internal career site. Please log into Workday and click on the Jobs Hub app or search for Browse Jobs.

Benefits: We offer competitive compensation along with a comprehensive benefits package, including medical, dental, vision and paid vacation/sick days, 401(k), generous employee pet discounts and more!

The information in this position description indicates the general nature and level of work to be performed. It is not designed to be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of associates assigned to this job. Management reserves the right to revise the job description or require that other tasks be performed when the circumstances of the job change (for example, emergencies, change in personnel, workload, or technical development).