Senior Data Scientist
Build and productionize machine learning models while developing LLM-powered, agentic analytics tools for business stakeholders. The role requires 5+ years of data science experience, strong Python and SQL skills, production ML expertise, and hands-on experience with LLM and agentic systems.
About the job
Responsibilities
- Build traditional machine learning models, including classification, regression, and anomaly detection, from proof of concept through production deployment.
- Own the model lifecycle, including feature engineering, validation, deployment, performance monitoring, drift detection, and retraining.
- Partner with engineering to productionize models within existing pipelines and platforms.
- Build internal analytics products such as dashboards, self-serve reporting, natural-language interfaces, and agentic tools.
- Develop LLM-powered and agentic applications with evaluation, monitoring, and appropriate human oversight.
- Drive stakeholder adoption through documentation, training, and enablement.
- Automate recurring analytical and modeling work with pipelines and monitoring systems.
- Write production-grade Python and SQL using version control, code review, testing, and CI/CD.
- Improve data quality, documentation, modeling standards, and AI-assisted analytics workflows.
Requirements
- 5+ years of professional data science experience or equivalent.
- Track record of shipping machine learning models and data products to production.
- Advanced SQL skills and experience with cloud data warehouses; BigQuery is preferred.
- Strong Python development skills.
- Hands-on experience with traditional machine learning models and production deployment.
- Strong statistical fundamentals, including feature engineering and validation methodology.
- Experience building with LLMs and agentic systems, including prompting, retrieval, tool use, and evaluation.
- Experience using AI coding agents such as Claude Code or Cursor.
- Demonstrated ability to drive adoption of tools among stakeholders.
- Strong communication skills with non-technical stakeholders.
- Ability to scope work independently and follow through to adoption.
Nice to Have
- Experience building or contributing to agent-based or LLM-powered analytics platforms.
- Experience in insurance, fintech, or another regulated domain.
- Experience building internal web tools or lightweight frontends for analytics products.
Compensation and Benefits
- Annual salary range of $125,000–$140,000.
- Equity based on role.
- Flexible paid time off and parental leave.
- 100% paid-premium option for medical, dental, and vision insurance.
- Lifestyle stipend supporting physical, emotional, and financial wellbeing.
Skills
Python, SQL, BigQuery, Machine Learning, Feature Engineering, Statistical Modeling, LLMs, Agentic Systems, Prompting, Retrieval-Augmented Generation, CI/CD, Model Monitoring
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