Director, Data Science
Fully Remote | Full-Time | Less than 10% Travel
Overview
Destination Pet is launching a new, PE-backed business unit focused on building a differentiated data platform for the pet health and pet services ecosystem. We are bringing together data from veterinary partners, pet care centers, boarding and daycare facilities, grooming locations, wellness providers, and other pet care channels to create meaningful insights and scalable data products. This is an opportunity to join the business at the ground floor and help shape how pet health and pet care data is transformed into valuable insights, products, and commercial opportunities.
About the Role
We are looking for a Director of Data Science to build the analytical foundation of this new business from the ground up. You will be a hands-on data science leader who can work with complex, fragmented, multi-source data and turn it into actionable insights and commercially valuable products. You will help define the data science strategy, build predictive and analytical models, identify opportunities to monetize data, and establish the tools, processes, and capabilities needed as the business grows. This role is ideal for someone who enjoys a builder environment—someone comfortable with ambiguity, excited by new challenges, and able to balance hands-on technical work with strategic thinking. Why You Should Apply You want to build something from the ground up rather than inherit an established data science function. You are excited about turning data and analytics into commercially valuable products. You enjoy working in an entrepreneurial, high-growth environment where priorities may evolve. You want the opportunity to influence the strategy, roadmap, tools, and future capabilities of a data science organization. You enjoy partnering with executives, product, technology, commercial, and operations teams. You are comfortable being both a hands-on data scientist and a strategic leader. You are interested in the opportunity to transform pet health and pet care data into meaningful insights. You want startup-like agility combined with the resources and backing of an established platform. You Might Not Be a Great Fit If You prefer working within a highly structured environment with clearly defined processes and priorities. You are looking for a role that is exclusively people-management or strategy-focused and does not require hands-on data science work. You are uncomfortable working with messy, fragmented, or incomplete datasets. You prefer focusing solely on technical analysis without partnering with commercial, product, operations, or executive stakeholders. You are not interested in connecting data science work to business outcomes and potential revenue opportunities. You find ambiguity and evolving priorities challenging. You prefer maintaining an existing data science function rather than building and shaping one. You Will Work On Data Science & Analytics Analyze large, complex, multi-source datasets related to pet health, veterinary care, pet services, customer behavior, and service utilization. Build predictive models, segmentation frameworks, forecasting tools, machine learning models, and other advanced analytical solutions. Identify trends, patterns, and commercial opportunities within complex datasets. Drive the creation of statistically differentiated predictive models. Data Products & Commercialization Partner with product, technology, commercial, operations, and executive teams to identify insights and data products that can be monetized. Support the development of data products that may be sold to external customers, partners, or industry stakeholders. Help turn fragmented pet care data into scalable products and commercially valuable insights. Data Quality & Infrastructure Work with internal and external data sources, including veterinary partners, pet care centers, customer systems, and third-party datasets. Lead efforts around data cleaning, normalization, deduplication, taxonomy creation, and quality control. Help establish best practices for data quality, privacy, governance, de-identification, and responsible data use. Help shape the future tools, structure, and capabilities of the data science function. Cross-Functional Leadership Translate complex analytical findings into clear, actionable insights for non-technical audiences. Collaborate across product, engineering, commercial, legal, operations, and executive teams. Operate effectively in a PE-backed environment focused on speed, accountability, value creation, and measurable outcomes.
What We're Looking For
Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Bioinformatics, or a related quantitative field. 6–10+ years of experience in data science, advanced analytics, machine learning, statistical modeling, or a related quantitative field. Strong proficiency in Python and/or R. Strong SQL skills and experience working with relational databases and large datasets. Experience working with messy, fragmented, or multi-source data. Demonstrated experience building predictive models, segmentation frameworks, forecasting models, machine learning models, or other advanced analytical solutions. Strong understanding of data quality, feature engineering, statistical inference, experimentation, model validation, and analytical best practices. Ability to communicate complex analysis clearly to executive, commercial, product, and non-technical stakeholders. Comfort working in a newly formed business, startup-like environment, or high-growth setting with ambiguity and evolving priorities. Preferred Experience Master's degree or PhD in a quantitative discipline. Experience in a startup, venture-backed company, PE-backed company, newly formed business, or corporate incubation environment. Experience building data products, commercial analytics products, data platforms, data marketplaces, or monetizable insight products. Experience in healthcare, veterinary medicine, pet care, life sciences, insurance, consumer health, retail, marketplace businesses, or multi-site services. Experience working with regulated, sensitive, privacy-conscious, or consumer data. Familiarity with privacy-preserving analytics, de-identification, aggregation, consent frameworks, and responsible data-use practices. Experience with cloud data platforms such as Snowflake, Databricks, AWS, GCP, Azure, or similar. Experience with BI and visualization tools such as Tableau, Power BI, Looker, Sigma, or similar.