Lead Data Scientist

Location: Hybrid — Newark, NJ (3 days/week onsite)

Employment Type: Contract-to-Hire

Pay Rate: $70-$85 per hour, based on experience. No C2C/1099. W2 only.

About the Role: 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 SQLWhat You Bring 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 Sage Maker 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, Lang Chain, Lang Graph, vector databases, Lang Fuse, and Agent Core Understanding of the model deployment lifecycle, A/B testing, CI/CD pipelines, and frameworks such as AWS Sage Maker and Azure Agentic AI tools