Leveraging advanced analytics and data science techniques to extract actionable insights and drive data-informed decision-making at HealthEquity.
Requirements
- Advanced developer in Python with expertise in pandas, scikit‑learn, and PySpark.
- SQL for large‑scale data processing.
- Building, tuning, and evaluating ML models; strong understanding of evaluation metrics.
- Vectorization/embeddings and vector search algorithms for NLP.
- Bias testing and fairness considerations.
- Expertise in prompt engineering and agentic AI concepts (LangGraph experience preferred).
- Model deployment concepts and MLOps practices (CI/CD, monitoring, reproducibility).
Responsibilities
- Build and tune ML models (classification, regression, clustering, recommenders).
- Develop LLM workflows: prompt engineering, RAG, fine‑tuning, multi‑modal models.
- Implement agentic AI solutions leveraging LangGraph for orchestration and tool‑use.
- Apply embeddings and vector search for NLP and retrieval pipelines.
- Process large datasets using Python (pandas, scikit‑learn, PySpark) and SQL.
- Apply MLOps practices: CI/CD, monitoring, reproducibility.
- Communicate insights clearly to technical and non‑technical audiences.
Other
- 4 to 5+ years of related experience in data science, preferably in a fast‑paced environment
- Translating business needs into modeling tasks; clear communication across audiences.
- Cross‑functional collaboration and Agile project experience with proper documentation.
- This is a remote position.
- Bachelor’s or Master’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, or related fields
