Lead Data Scientist

Job Description

Lead Data Scientist

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

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Employment Type: Contract-to-Hire

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

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About the Role

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• 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

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• Implement Machine Learning, AI, and agentic capabilities that deliver stability, scalability, and integration across products and services

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• Solve sophisticated business problems and deploy innovative products and experiences

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What You'll Do

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• Provide deep technical leadership across a portfolio of high-impact data science initiatives

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• Identify optimal data, models, and training/testing techniques for successful product delivery

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• Manage team members across data analysis, model development (traditional ML and statistical models), GenAI and agent development, testing, training, and tuning

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• Write production-grade code and partner with ML engineers to push models into production, including traditional ML, statistical models, GenAI, and agentic solutions

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• 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

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• Communicate model design and development clearly to technical and non-technical audiences

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• Leverage CI/CD best practices, including test automation and monitoring, for ML model and application deployment

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• Stay current on emerging technologies and embed learning/innovation into the team's daily work

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• Program primarily in Python and SQL

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What You Bring

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• Advanced degree (Master's or Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial Science, Data Science, or a related quantitative field

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• Experience leading a small team with minimal guidance

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• Demonstrated ability to mentor team members and manage operations based on project and resourcing needs

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• Ability to influence business stakeholders and drive adoption of AI/ML solutions

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• Experience with Agile methodologies and Test-Driven Development (TDD)

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• Strong business acumen to support sound, context-driven decision-making

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• Excellent problem-solving, communication, and collaboration skills

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• Experience with cloud-based AI platforms such as Bedrock and SageMaker

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Preferred Technical Expertise (several of the following)

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• Data acquisition and transformation using APIs, semantic data models, SQL, and Python

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• Database management across relational (SQL), unstructured (NoSQL), and graph/ontology (Graph DB) systems

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• Data analysis using visualization, manipulation, and statistical methods to identify trends and anomalies

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• Strong foundation in multivariable calculus, linear algebra, differential equations, applied probability, and applied statistics

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• Deep understanding of machine learning theory, including supervised and unsupervised models

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• Experience with Generative AI and NLP, including RAG, LangChain, LangGraph, vector databases, LangFuse, and AgentCore

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• Understanding of the model deployment lifecycle, A/B testing, CI/CD pipelines, and frameworks such as AWS SageMaker and Azure Agentic AI tools

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