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About the Role

The Data Science team applies modern AI and machine learning techniques to develop practical, high-impact solutions that help the business adapt, innovate, and operate at scale.

Responsibilities

• Build, test, and deploy production-grade AI and machine learning solutions using both classical methods and generative AI approaches, including LLMs, RAG, fine-tuning, prompt optimization, and agentic workflows.
• Conduct applied research to evaluate new AI and machine learning techniques for complex business problems and identify practical opportunities for adoption.
• Design and implement evaluation frameworks to measure model quality, robustness, reliability, and business impact.
• Partner closely with product managers, data engineers, and business stakeholders to translate research findings and business needs into scalable, production-ready solutions.
• Contribute to real-time and batch data pipeline workflows in collaboration with data engineering, and support monitoring, logging, metrics, guardrails, and human-in-the-loop review processes.
• Communicate technical concepts, research outcomes, and recommendations clearly to both technical and non-technical audiences.
• Stay current with emerging AI and machine learning developments and apply relevant advances thoughtfully to ongoing work.
• Maintain high standards for code quality, documentation, and review practices to support reliability and long-term maintainability.

Requirements

• 3+ years of industry or applied research experience.
• Strong foundation in machine learning, deep learning, natural language processing, statistical analysis, algorithms, and data structures.
• Hands-on experience building and deploying AI and machine learning solutions, ideally including LLMs, generative AI, prompt engineering, RAG, fine-tuning, and agentic systems.
• Strong Python programming skills and experience with frameworks such as PyTorch, TensorFlow, JAX, or scikit-learn.
• Familiarity with LLM and AI application frameworks such as Hugging Face, LangChain, and LlamaIndex.
• Experience working with at least one cloud platform.
• Knowledge of vector databases, big data ecosystems, and MLOps or LLMOps tooling.
• Exposure to AI-assisted coding tools such as Claude, Codex, GitHub Copilot, or Cursor.
• Strong communication skills, sound judgment, and the ability to work independently, manage ambiguity, and learn quickly in a fast-moving environment.

Skills

• AI
• Machine Learning
• Generative AI
• LLMs
• RAG
• Fine-tuning
• Prompt optimization
• Agentic workflows
• Deep learning
• Natural Language Processing
• Statistical analysis
• Algorithms
• Data structures
• Python
• PyTorch
• TensorFlow
• JAX
• scikit-learn
• Hugging Face
• LangChain
• LlamaIndex
• Cloud platforms
• Vector databases
• Big data ecosystems
• MLOps
• LLMOps
• Claude
• Codex
• GitHub Copilot
• Cursor

Location

• New York

Work Type

• Full-time

Experience Level

• 3+ years

Education Level

• MS or PhD in Computer Science, Data Science, Statistics, Operations Research, or a related STEM field

Salary/Compensations

• $175,000 to $250,000

Benefits

• Base salary
• Discretionary performance bonus
• Comprehensive benefits

About the Company

• Millennium is a global, diversified alternative investment firm, founded in 1989.
• Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors.
• Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning.
• With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time.
• Discover how transformative growth accelerates impact.
• The Information Technology team is core to the health and growth of Millennium’s business.
• Supporting the firm’s active, multi-manager model, the team builds and advances flexible, scalable technology and proprietary systems that power next-generation analytical, data, and trading capabilities.