> Markdown version of [/jobs/ext/3660191-data-science-remote-opportunity](https://www.wearedevelopers.com/jobs/ext/3660191-data-science-remote-opportunity). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Science - Remote Opportunity - **Company:** TRENT HOEK OUTDOORS LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $180,000.0 - $210,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Microsoft Azure, Big Data, Bioinformatics, Data Cleansing, Data Deduplication, Data Integrity, Data Visualization, Relational Databases, Database Queries, Python (Programming Language), Machine Learning, Power BI, Cloud Services, Standard Sql, Tableau (Software), Google Cloud, Feature Engineering, Snowflake, Model Validation, Information Technology, Data Management, Looker Analytics, Databricks - **Published:** October 9, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/ppzz0wwx8d ## About the Role * Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, Economics, Bioinformatics, or a related quantitative field. ### Experience * 6-10+ years of experience in data science, advanced analytics, machine learning, statistical modeling, or a related quantitative field. * Experience working with messy, fragmented, multi-source data and transforming it into usable analytical assets. * Demonstrated experience building: * Predictive models * Segmentation frameworks * Forecasting models * Machine learning models * Advanced analytical solutions * Experience applying statistical and analytical best practices, including model validation, feature engineering, statistical inference, experimentation, and data quality. * Experience working in a newly formed business, startup-like environment, or high-growth setting with ambiguity and evolving priorities. ### Technical Skills * Strong proficiency in Python and/or R. * Strong SQL skills. * Experience working with relational databases and large datasets. * Strong knowledge of data cleaning, normalization, quality control, feature engineering, statistical modeling, and predictive analytics. ### Leadership & Communication * Ability to communicate complex analytical findings clearly to executive, commercial, product, and non-technical stakeholders. * Strong business judgment and ability to prioritize high-value analytical opportunities. * Ability to work independently while collaborating effectively across functions. * Hands-on approach combined with the ability to help define data science strategy and future capabilities. ## Preferred Qualifications * Master's degree or PhD in a quantitative discipline. * Experience in a startup, venture-backed company, private-equity-backed company, newly formed company, 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. * Experience partnering with product, engineering, commercial, legal, operations, and executive teams. ## Ideal Candidate Profile * Builder mindset with the ability to create structure in an early-stage environment. * Commercially curious and interested in turning data into revenue-generating products. * Comfortable working hands-on while defining strategy and future team capabilities. * Strong business judgment and ability to focus on the highest-value analytical opportunities. * Comfortable operating in a PE-backed environment focused on speed, accountability, value creation, and measurable outcomes. * Able to work independently in a fully remote environment while collaborating across functions. * Passionate about transforming pet health and pet care data into meaningful insights. ## Core Skills * Data Science and Machine Learning * Predictive Modeling * Statistical Analysis * SQL * Python and/or R * Data Cleaning and Normalization * Data Quality and Quality Control * Feature Engineering * Statistical Inference and Experimentation * Data Product Development * Commercial Analytics * Data Monetization * Executive Storytelling and Insight Presentation * Privacy-Aware and Ethical Data Use * Cloud Data Platforms * Cross-Functional Collaboration * Startup, New Business Unit, and PE-Backed Operating Experience ## Description Destination Pet is launching a new, private-equity-backed business unit focused on building a differentiated data platform for the pet health and pet services ecosystem. The platform will collect, organize, analyze, and commercialize data from veterinary partners, pet care centers, boarding and daycare facilities, grooming locations, wellness providers, and other pet care channels., * Define and build the data science strategy for the newly formed pet health data business unit., * Build predictive models, segmentation models, forecasting tools, and other advanced analytical solutions to identify trends, patterns, and commercial opportunities. * Partner with product, technology, commercial, operations, and executive stakeholders to identify data products and insights that can be monetized. * Support the development of data products for external customers, partners, and industry stakeholders. * Work with internal and external data sources, including veterinary partners, pet care centers, customer systems, and third-party datasets. * Lead cross-functional efforts involving data cleaning, normalization, deduplication, taxonomy creation, and quality control. * Establish processes for ongoing data integrity and monitoring. * Translate complex analytical findings into clear, actionable insights for executive and non-technical audiences. * Establish best practices for responsible data use, privacy, governance, de-identification, and data quality. * Operate effectively in an entrepreneurial environment with evolving business models and priorities. * Drive the creation of statistically differentiated predictive models supported by strong research and data science practices. * Help shape the future structure, tools, capabilities, and analytical roadmap of the data science function as the business scales.