Senior Data Scientist

SEI is seeking a highly skilled and experienced Senior Data Scientist to join our enterprise Artificial Intelligence team. In this role, you will lead data-driven initiatives, develop advanced models, and deliver actionable insights that directly impact our business strategy. You will work closely with cross-functional teams, mentoring junior data scientists and contributing to the overall Artificial Intelligence vision at SEI.  What you will do: Lead the end-to-end product development lifecycle, from ideation to launch, ensuring the successful delivery of AI products. Design, deploy, and monitor machine learning models in production using MLOps tools and cloud-native services. Develop and fine-tune Generative AI models and LLMs, integrating them into business applications. Clean, preprocess, and analyze large datasets to extract meaningful patterns, trends, and insights. Conduct thorough exploratory data analysis to discover hidden insights and potential opportunities. Build and maintain data pipelines for efficient data collection, storage, and processing. Develop and implement machine learning algorithms and models for predictive and prescriptive analytics. Communicate complex findings to both technical and non-technical stakeholders through visualizations, reports, and presentations. Stay up-to-date with the latest advancements in artificial intelligence, machine learning, and relevant technologies. Build scalable, automated data pipelines for batch and real-time analytics using tools like Airflow, Spark, or dbt. Ensure compliance with data privacy and security standards in all AI solutions. What we need from you: Bachelor's degree from an accredited college or university, and/or equivalent relevant experience. MS, MBA or CFA designation is a plus. A minimum of 5 years of experience in data science, machine learning, or a related field. Wealth management industry related experience is a plus. Strong understanding of AI technologies, including machine learning, natural language processing, and Generative AI. Experience with MLOps platforms (MLflow, Kubeflow, Vertex AI, Azure ML), containerization (Docker), and orchestration (Kubernetes). Hands-on experience with Generative AI, LLMs, and prompt engineering. Familiarity with modern data engineering tools (Airflow, Spark, Kafka, dbt). Knowledge of data privacy regulations and responsible AI practices. Proficiency in programming languages such as Python or R, and experience with machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Strong experience with data manipulation tools (e.g., SQL, pandas). Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib). Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps best practices. Detail oriented with the ability to organize and prioritize tasks to ensure timely delivery of the projects What we would like from you: Proven decision-making and problem-solving skills.