Data Scientist

Job Title

A Data Scientist

Pay

The annual base salary range for this position in California is $100,000 to $140,000 per year.

Responsibilities

• Own the full analytical lifecycle, from problem definition and data extraction through modeling, visualization, and stakeholder presentation
• Define, instrument, and track metrics that measure business initiative success and drive decision-making across the organization
• Design and execute experiments end-to-end, including hypothesis formation, test design, execution, and translation of results into clear, defensible recommendations
• Build and maintain Power BI dashboards that give business teams a trusted, self-serve view of performance data
• Develop and deploy analytical models, including regression, classification, forecasting, or clustering, in real-world production context
• Apply AI and LLM-powered tooling to accelerate data workflows and give business teams faster answers from complex data
• Partner with cross-functional teams to translate business objectives into data problems and data findings into decisions

Qualifications

• 3–5 years of hands-on analytical experience delivering production-grade work
• Academic background in hard science, such as physics, mathematics, computer science, engineering, or a related quantitative field
• Production-grade Python and advanced SQL experience, with strong attention to performance, reproducibility, and maintainable code
• Practical experience applying statistics, including building and validating models, diagnosing failures, and explaining results to non-technical stakeholders without losing rigor
• Hands-on experience with Power BI or equivalent tools, including dashboards others depend on daily, not proof-of-concepts
• Demonstrated AI fluency, including experience building something with LLMs or generative AI in a real context, not just following a tutorial
• Strong written and verbal communication skills, with the ability to present complex findings clearly to any audience
• AI-native mindset, with experience using AI-assisted tooling as a genuine productivity multiplier, not a novelty