VP, Data Science
United States · Remote · Permanent
Heads up: this posting is for future opportunities rather than one specific open role. If you apply, we'll add you to our candidate network and may reach out when relevant roles come up.
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What the market looks like
We've tracked 100+ senior-level data science postings across the US in the last six months, with strongest hiring concentrated in California, New York, and Washington. Organizations are building data science teams at scale, particularly in technology, financial services, and professional services. Compensation for this level typically lands between $190K and $350K annually. The strongest candidates bring proven experience scaling data science functions, shipping production ML systems, and translating complex analytical work into business outcomes—not just technical depth, but the ability to recruit, mentor, and align technical work with organizational strategy.
Job responsibilities
Lead and grow a data science team: hire, mentor, and develop talent; set technical direction; build a culture of ownership and rigor
Own the strategic roadmap for data science initiatives; partner with product, engineering, and business leadership to prioritize high-impact projects
Drive end-to-end delivery of ML and analytics products; ensure models move from experimentation to production and deliver measurable business value
Establish data science best practices: code quality, reproducibility, documentation, and cross-team collaboration standards
Build relationships across the org; translate business problems into data science problems and communicate results to non-technical stakeholders
Evaluate and integrate new tools, frameworks, and methodologies; keep the function current with evolving ML and data engineering landscapes
Define and track success metrics; demonstrate ROI of data science work and inform resource allocation decisions
Candidate requirements
8+ years of experience in data science, analytics, or machine learning roles, with at least 3+ years leading or managing a data science team
Proven track record shipping production ML systems and analytics products that drove measurable business outcomes
Strong technical foundation in statistics, modeling, and programming; fluency with Python, SQL, and modern ML frameworks
Demonstrated ability to recruit, build, and lead high-performing teams; experience mentoring junior data scientists and fostering technical growth
Excellent communication skills; ability to translate between technical depth and business-facing storytelling for diverse audiences
Experience working in fast-moving or complex organizations; comfort with ambiguity and iterative problem-solving