Data Scientist

FSAStore.com

37d•$130,000 - $185,000•Remote

About The Position

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.

Requirements

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.
BA/BS in Computer Science, Data Science, Mathematics, Engineering, Economics or other technical function. Masters or PhD preferred.

Nice To Haves

Experience in e-commerce, marketing, or digital health is highly desirable.

Responsibilities

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.