Data Scientist
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.
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.
