Envestnet is seeking a Senior Data Scientist to design and deploy machine learning solutions that power Envestnet’s products and tools, combining advanced analytics, AI/ML techniques, and wealth domain expertise to deliver intelligent, scalable solutions.
Requirements
- Proficiency in Python, SQL, and ML frameworks (scikit-learn, XGBoost, NLP/transformers).
- Experience with large datasets, statistical modeling, and cloud ML platforms (AWS, Snowflake).
- Knowledge of graph technologies (Neo4j, RDF/OWL, SPARQL) and MLOps tools (MLflow, Airflow, dbt)
- Experience with LLM integration and retrieval-augmented generation (RAG) for enterprise applications.
- Expertise in graph algorithms (community detection, link prediction) and embeddings (node2vec, graphSAGE).
- Strong understanding of model risk management, including explainability (SHAP), fairness, and compliance implications.
- Hands-on experience with orchestration tools (Airflow, Prefect) and CI/CD for ML pipelines.
Responsibilities
- Work independently or in team to solve complex problems and create scalable models/algorithms that will be integrated into Envestnet’s tools and products
- Develop and deploy advanced ML models (predictive analytics, NLP, LLM-based solutions) to enhance Envestnet’s products and tools.
- Engineer features and transform data from complex wealth datasets (accounts, tax-lots, corporate actions) to ensure model accuracy and compliance.
- Leverage knowledge graph techniques (RDF/OWL, SPARQL, Cypher) for entity resolution, semantic modeling, and graph-based insights (e.g., householding, cross-sell).
- Implement retrieval-augmented generation (RAG) and LLM-driven solutions for intelligent content and advisor-facing insights.
- Ensure model governance and compliance by applying explainability (SHAP), fairness checks, and regulatory considerations (Reg BI, GDPR/CCPA).
- Collaborate with engineering and QA teams to integrate models into production using scalable pipelines (Airflow, dbt, MLflow).
Other
- This is a hybrid role, with in-office work required at either our Berwyn, PA or Raleigh, NC office location.
- 5+ years in Data Science, Machine Learning, or AI roles.
- Familiarity with wealth management domain and regulatory context (Reg BI, GDPR/CCPA).
- Influence product strategy through actionable insights and clear communication with senior leadership and stakeholders.
- Contribute to the development of the data science product strategy by incorporating input from business leaders, data leaders, and senior leadership, while supporting the execution and alignment of the product roadmap.
