Senior Data Scientist
United States · Remote · Permanent
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What the market looks like
We've tracked 13,400+ specialist-level data science postings across the US in the last six months. Hiring concentrates in technology hubs like California, New York, and Washington, with strong secondary demand across financial services, professional services, and healthcare. Specialist-level data scientists in this cohort command salaries between $160k and $310k. The strongest candidates combine deep technical fluency in statistical modeling and machine learning with the ability to translate business problems into data-driven solutions, ship production systems, and partner effectively across engineering and product teams.
Job responsibilities
Own end-to-end data science projects—from problem definition and exploratory analysis through model development, validation, and deployment into production systems
Build and maintain machine learning models that drive measurable business impact, including feature engineering, model selection, and performance optimization
Partner with engineering and product teams to integrate models into applications and data pipelines, ensuring scalability and reliability
Design and execute experiments (A/B tests, causal inference studies) to validate hypotheses and inform product and business decisions
Communicate findings and recommendations to non-technical stakeholders, translating complex analyses into actionable insights
Lead or contribute to data infrastructure improvements, working with engineers to reduce model training time, improve data quality, and streamline workflows
Mentor junior team members and contribute to data science best practices across the organization
Candidate requirements
5–8 years of professional data science experience, including hands-on work building and deploying production machine learning models
Strong foundation in statistics, experimental design, and machine learning fundamentals; fluency in Python or R and SQL
Demonstrated ability to work across the full model lifecycle—from scoping and feature engineering through validation, deployment, and monitoring
Proven track record shipping models or analyses that directly influenced business outcomes or product decisions
Clear communication skills; ability to explain technical work and uncertainty to both technical and non-technical audiences