Data Scientist
Role overview
We're looking for a hard-working, thoughtful Data Scientist who delivers results. You'll transform messy data into useful models and decision-making tools, collaborate closely with engineering and business development teams, and own projects from start to finish—including scoping, deployment, and monitoring.
In Business Development at Millennium, we identify and onboard trading talent and data advantages that drive profitability. We evaluate data vendor solutions and surface novel data points that create early, differentiated signals ahead of competitors. Some work involves delivering reliable, established solutions, while much of it is creative—extracting hidden insights from existing data and discovering new sources.
Strong Python skills are required. Hands-on experience with large language models (LLMs) and their practical applications is a significant plus. We value humility, reliability, clear communication, and collaborative teamwork.
Responsibilities
- check_circle Own outcomes: break projects into milestones, estimate realistically, meet deadlines, and surface risks early with options.
- check_circle Build and deploy models: develop ML models (including LLM-enabled solutions when appropriate), design features, evaluate rigorously, and contribute to production-grade pipelines.
- check_circle Work the full data lifecycle: wrangle and clean data, implement data quality checks, write maintainable Python/SQL, add tests, and document decisions.
- check_circle Collaborate cross-functionally: translate business questions into analysis, present trade-offs clearly, and iterate with stakeholders and tech partners.
- check_circle Deploy to production: partner with data engineers to ship to production (APIs, batch jobs, monitoring) and create feedback loops for continuous improvement.
- check_circle Drive system improvements: propose pragmatic improvements to data, tooling, and process that reduce manual work and increase reliability.
Basic qualifications
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
- 3+ years of hands-on experience in data science, analytics, or ML, with at least one end-to-end project shipped to production used by real stakeholders.
- Strong Python proficiency (Pandas, NumPy, Matplotlib, and Scikit-learn).
- Sound understanding of ML fundamentals: problem framing, validation, metrics, overfitting, feature engineering.
- Experience with SQL and NoSQL database structures along with relational, columnar and document databases.
- Experience with LLMs and modern NLP: prompt engineering, retrieval-augmented generation (RAG), vector databases, knowledge graphs—plus a pragmatic sense of when not to use them.
- Strong data visualization and storytelling abilities using tools such as Plotly, Dash, Streamlit, or similar frameworks.
- Familiarity with cloud services (AWS/Azure) for data storage, compute, and deployment.
Benefits
- check_circle The estimated base salary range for this position is $165,000 to $250,000, which is specific to New York and may change in the future.
- check_circle Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package.
- check_circle When finalizing an offer, we take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package.
Tags & Focus Areas
About Millennium Management
We’re seeking an AI Platform Engineer to contribute to the development and management of cutting-edge AI infrastructure for our complex enterprise environment. In this role, you’ll harness your expertise to build infrastructure which enables your team and the firm to manage autonomous agents, machine learning systems and other applications in the AI domain.
Ready to Join the Team?
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