• Design the infrastructure to move, clean, and store data for analysis. • Build and maintain models for credit risk, fraud detection, user behavior, and portfolio performance • Data quality monitoring • Partner with Product, Finance, Engineering and Compliance to embed data into decision-making • Define and track core business, risk, and growth metrics • Design experiments and analyses to improve unit economics and customer outcomes • Ensure data quality, governance, and scalable analytics infrastructure • Mentor junior analysts and help establish data best practices

About the Role: Health-E Commerce is seeking a Data Scientist to help shape the future of our modern data ecosystem. As a critical member of our centralized Data & Analytics team, you will be our primary expert in statistical modeling, machine learning, and AI applications built on top of our proprietary data platform leveraging unique first-party data. Reporting directly to the SVP of Data Science & Analytics, you will play a critical role in building out our key Data Science assets that are direct contributors to revenue, ranging from marketing measurement and optimization, site optimization and personalization, and forecasting. As one of the founding members of the Data Science team, you will work cross-functionally across marketing, finance, merchandising, and product. What You'll Do: - Statistical Modeling: Design and implement advanced statistical models for applications such as demand forecasting, regression analysis, and probabilistic sampling to solve real-world business challenges. - Machine Learning: Own the end-to-end ML lifecycle—feature engineering, model training, hyperparameter tuning, and deployment. Work with supervised, unsupervised, and ensemble methods to optimize performance across marketing, personalization, and operational use cases. - AI Applications: Explore and implement cutting-edge AI techniques (e.g., NLP, recommendation systems, generative models) for exploratory work in GenAI. - Data Modeling & Visualization: Collaborate with Data Engineering to ensure robust data pipelines for feature engineering and modeling. Partner with Analytics to deliver interactive dashboards and visualizations that integrate seamlessly with existing tools. - Business Insights: Translate complex technical outputs into actionable insights for stakeholders. Frame ambiguous business problems into testable hypotheses and communicate findings in clear, non-technical language without losing nuance. - Innovation & Thought Leadership: Stay ahead of industry trends in ML/AI and proactively identify opportunities to apply emerging technologies to Health-E Commerce’s ecosystem. What You'll Bring: - Minimum of 4+ years of experience in data science, statistical modeling, machine learning, AI or related experience. - Strong Python and SQL experience ; experience with ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). - Hands-on experience with advanced methods such as boosted decision trees, neural networks, clustering, and stochastic simulation. - Experience with various cloud data platforms working with data at scale and as part of end-to-end pipelines (e.g., Snowflake, Databricks, Azure Synapse, BigQuery, Microsoft Fabric). - Experience deploying ML models into production, including MLOps and model maintenance. - Proficiency in data visualization in at least one popular platform (Tableau, PowerBI, etc.) - Experience working as part of an end-to-end data team, with proven ability to collaborate across technical teams in data engineering, product, analytics, and technology. - Strong experience working in agile methodologies and using tools like Jira. - Proven ability to translate business needs into technical requirements and to explain technical models into actionable insights. Exceptional communication and stakeholder management skills. - Strong ability to translate ambiguous problems and translate into clear problem statements. - Experience in e-commerce, marketing, or digital health is highly desirable. - BA/BS in Computer Science, Data Science, Mathematics, Engineering, Economics or other technical function. Masters or PhD preferred. Compensation, Benefits, & Additional Details: Health-E Commerce's compensation philosophy is grounded in market data and internal equity to ensure fairness and consistency across the team. Individuals new to the company should generally expect offers to fall between the entry point and midpoint of the salary range. Our goal is to provide an offer that supports growth potential within the role and allows for future salary progression. - Compensation: $130,000-185,000 - Discretionary Annual Bonus Eligibility: Up to 15% - Medical, Dental, Vision, and 401K with a company match - Dependent Care, FSA & HSA accounts - Paid Parental & Bonding Leave - Flexible PTO & office closure on all major holidays - Monthly wellness & internet reimbursements - Professional development including certification support & leadership coaching - Mental Health resources - 100% remote within the United States - Must be able to work EST hours Candidate Privacy Notice

• Assist with all data management project management-related activities • Support closeout/lock of study databases • Execute study activities including database verification and data transfer validation • Prepare and deliver routine and interim/final data transmissions

• Support applied research, evaluation, and technical assistance projects within the Learning Supports program. • Contribute to data-driven work focused on improving K–12 educational systems. • Build data pipelines and cloud-based applications. • Conduct quantitative and qualitative analyses. • Develop visualizations and reports. • Ensure data quality and reproducibility across studies. • Collaborate with federal and state agencies, school districts, and foundations.