Senior Data Scientist

Overview Envestnet is seeking a Senior Data Scientist to join our Product department. This is a hybrid role, with in-office work required at either our Berwyn, PA or Raleigh, NC office location. Envestnet is transforming the way financial advice is delivered through its connected technology, advanced insights, and asset management solutions – backed by industry-leading service and support. Since 1999, Envestnet has served the wealth management industry and today supports trillions in platform assets, serving over a hundred thousand financial advisors. The vast majority of the nation’s leading banks, the largest wealth management and brokerage firms, and over 500 of the largest RIAs rely on Envestnet’s wealth management platform and solutions to drive business growth, boost productivity, and deliver better financial outcomes for their clients. Job Summary We are seeking a Senior AI/Data Scientist to design and deploy machine learning solutions that power Envestnet’s products and tools. This role combines advanced analytics, AI/ML techniques, and wealth domain expertise to deliver intelligent, scalable solutions. The position also requires cross-functional collaboration with engineering and quality assurance teams to ensure successful implementation and delivery. Job 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) Stay current with AI/ML advancements and apply best practices in MLOps, model monitoring, and drift detection 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 Adherence to and application of Envestnet legal, compliance, risk, business continuity and administrative policy within the role and department(s) including the timely completion of training & awareness, affirmations and testing as requested As part of the responsibilities for this role, you will understand and readily support Envestnet's established corporate business practices, policies, internal controls and procedures designed to create value or minimize risk Required Qualifications 5+ years in Data Science, Machine Learning, or AI roles Proficiency in Python, SQL, and ML frameworks (scikit-learn, XGBoost, NLP/transformers) Experience with large datasets, statistical modeling, and cloud ML platforms (AWS, Snowflake) Familiarity with wealth management domain and regulatory context (Reg BI, GDPR/CCPA) Knowledge of graph technologies (Neo4j, RDF/OWL, SPARQL) and MLOps tools (MLflow, Airflow, dbt) Wealth domain fluency including understanding of client → household → advisor hierarchies; legal entities; account types; tax-lots, corporate actions, fee schedules, and billing Product knowledge: equities/ETFs/mutual funds/SMAs/UMAs/alternatives; model portfolios; rebalancing & overlay Regulatory context: Reg BI, SEC/FINRA recordkeeping, KYC/AML basics, privacy (Reg S-P, GDPR/CCPA) Core workflows: onboarding/householding, performance (GIPS concepts), goal-based planning, suitability/risk profiling, surveillance, and advisor productivity Preferred Qualifications 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 Familiarity with industry standards (FIBO, FIX, ISO 20022) and semantic modeling for wealth data Ability to translate complex AI outputs into business insights and communicate effectively with senior stakeholders Envestnet Envestnet is an Equal Opportunity Employer. Compensation & Benefits Competitive Compensation/Total Reward Packages Health Benefits (Health/Dental/Vision) Paid Time Off (PTO) & Volunteer Time Off (VTO) 401K – Company Match Annual Bonus Incentives Parental Stipend Tuition Reimbursement Student Debt Program Charitable Match Wellness Program Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology #J-18808-Ljbffr