Lead Data Scientist

• Join a leading investment firm as a Lead Data Scientist, partnering with Machine Learning Engineers, Data Engineers, Data Analysts, and cross-functional teams to build AI and Machine Learning products
• Implement Machine Learning, AI, and agentic capabilities that deliver stability, scalability, and integration across products and services
• Solve sophisticated business problems and deploy innovative products and experiences

What You’ll Do

• Provide deep technical leadership across a portfolio of high-impact data science initiatives
• Identify optimal data, models, and training/testing techniques for successful product delivery
• Manage team members across data analysis, model development (traditional ML and statistical models), GenAI and agent development, testing, training, and tuning
• Write production-grade code and partner with ML engineers to push models into production, including traditional ML, statistical models, GenAI, and agentic solutions
• Work hands-on with Agentic AI systems, fine-tuning techniques (e.g., LoRA), LLM deployment, RAG, Agentic RAG, Strands, Claude Agents SDK, and related agentic concepts
• Communicate model design and development clearly to technical and non-technical audiences
• Leverage CI/CD best practices, including test automation and monitoring, for ML model and application deployment
• Stay current on emerging technologies and embed learning/innovation into the team’s daily work
• Program primarily in Python and SQL

• Advanced degree (Master’s or Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial Science, Data Science, or a related quantitative field
• Experience leading a small team with minimal guidance
• Demonstrated ability to mentor team members and manage operations based on project and resourcing needs
• Ability to influence business stakeholders and drive adoption of AI/ML solutions
• Experience with Agile methodologies and Test-Driven Development (TDD)
• Strong business acumen to support sound, context-driven decision-making
• Excellent problem-solving, communication, and collaboration skills
• Experience with cloud-based AI platforms such as Bedrock and SageMaker

Preferred Technical Expertise (several of the following)

• Data acquisition and transformation using APIs, semantic data models, SQL, and Python
• Database management across relational (SQL), unstructured (NoSQL), and graph/ontology (Graph DB) systems
• Data analysis using visualization, manipulation, and statistical methods to identify trends and anomalies
• Strong foundation in multivariable calculus, linear algebra, differential equations, applied probability, and applied statistics
• Deep understanding of machine learning theory, including supervised and unsupervised models
• Experience with Generative AI and NLP, including RAG, LangChain, LangGraph, vector databases, LangFuse, and AgentCore
• Understanding of the model deployment lifecycle, A/B testing, CI/CD pipelines, and frameworks such as AWS SageMaker and Azure Agentic AI tools