Data Scientist

Millennium; New York (NY); On-site; USD 165,000 - 250,000; Full time

Benefits offered by this job

Performance bonus

Comprehensive benefits package

Job summary

Millennium in New York is seeking an experienced Data Scientist to transform messy data into actionable models and decision tools. You will own projects end-to-end, from scoping to deployment and monitoring, while collaborating with engineering and business development teams.

The role emphasizes strong Python skills and hands-on work with large language models, plus a collaborative, reliable teammate who communicates clearly and shares knowledge.

Qualifications

• Bachelor's degree in CS/Data Science/Statistics or related field.
• 3+ years of hands-on data science with at least one production project.
• Strong Python experience (Pandas, NumPy, Matplotlib, Scikit-learn).
• Experience with LLMs and modern NLP approaches is a plus.

Responsibilities

• Own projects end-to-end from scoping to deployment and monitoring.
• Build and deploy ML models, including LLM-enabled solutions when appropriate.
• Wrangle data, implement quality checks, and write maintainable Python/SQL.
• Collaborate with engineering and business stakeholders to translate questions into analysis.
• Deploy to production via APIs or batch jobs and establish feedback loops.
• Drive improvements to data, tooling, and processes to reduce manual work.

Skills

Python

Machine Learning

Data Visualization

Collaboration

Education

Bachelor's degree in Computer Science, Data Science, Statistics, or related field

Tools

Plotly

Dash

Streamlit

Job description

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

• Own outcomes: break projects into milestones, estimate realistically, meet deadlines, and surface risks early with options.
• Build and deploy models: develop ML models (including LLM-enabled solutions when appropriate), design features, evaluate rigorously, and contribute to production‑grade pipelines.
• Work the full data lifecycle: wrangle and clean data, implement data quality checks, write maintainable Python/SQL, add tests, and document decisions.
• Collaborate cross‑functionally: translate business questions into analysis, present trade‑offs clearly, and iterate with stakeholders and tech partners.
• Deploy to production: partner with data engineers to ship to production (APIs, batch jobs, monitoring) and create feedback loops for continuous improvement.
• Drive system improvements: propose pragmatic improvements to data, tooling, and process that reduce manual work and increase reliability.

Qualifications/Skills Required

• 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.

How We Work (what Success Looks Like)

• Strong ownership: Plan thoroughly, communicate proactively, and meet deadlines—we value reliability over last‑minute heroics
• Humble and collaborative: Seek and provide constructive feedback, write clear documentation, and pair program when it helps the team
• Bias toward action: Start simple, deliver iteratively, and improve based on evidence

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. Millennium pays a total compensation package which includes a base salary, discretionary performance bonus, and a comprehensive benefits package. 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.