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Staff Data Scientist United States, San Francisco Jobs

9 Job Offers

Staff Data Scientist, Forward Deployed
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Lead strategic customer engagements as a Staff Data Scientist in San Francisco. Requires 10+ years deploying ML models in production, strong Python/SQL skills, and forward-deployed or consulting experience with messy customer data.
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6sense
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Staff Data Scientist, Marketing Analytics
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Lead marketing analytics for a 9-figure paid media budget at Chime in San Francisco. Own attribution, incrementality, MMM and experimentation strategy, guiding budget decisions across Marketing, Growth and Finance teams.
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Chime Financial, Inc
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Staff Data Scientist - RiskOS
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Socure
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Staff Data Scientist - Product Analytics
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Ironclad
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Staff Data Scientist
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Taskrabbit
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Staff Product Data Scientist, Paid Media
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Location
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a16z
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Staff Product Data Scientist, Lending
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Cash App
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Member Of Technical Staff (Data Scientist)
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Join Perplexity as a Member of Technical Staff (Data Scientist) in San Francisco. We seek 6-8+ years of experience in data science or analytics engineering, with deep SQL expertise and a builder mentality. You'll build AI agents that autonomously conduct full analyses—from hypothesis to recommend...
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175000.00 - 330000.00 USD / Year
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Perplexity
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Staff Data Scientist, Airports and Travel
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As a Staff Data Scientist at Uber, you will be a strategic thought leader for the Airports and Travel segment, tackling complex challenges in the end-to-end traveler experience. This role requires expert proficiency in Python, SQL, and advanced experimentation (A/B testing, causal inference) to i...
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216000.00 - 240000.00 USD / Year
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Uber
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About the Staff Data Scientist role

Discover the pinnacle of data-driven careers with Staff Data Scientist jobs. This senior-level role represents a critical leadership position within technology and data science teams, where professionals translate complex data into transformative business strategy and scalable machine learning solutions. Staff Data Scientists operate at the intersection of advanced analytics, engineering, and cross-functional leadership, driving innovation and measurable impact across entire organizations.

Typically, individuals in this profession are entrusted with end-to-end ownership of high-stakes data science initiatives. Common responsibilities include architecting and deploying sophisticated machine learning models into production environments, ensuring they are robust, scalable, and deliver continuous value. They conduct deep exploratory data analysis to uncover hidden insights and identify new opportunities for growth, optimization, or product enhancement. A key aspect of the role involves defining key performance indicators and north-star metrics, then designing and analyzing A/B tests and experiments to directly influence business outcomes. Furthermore, Staff Data Scientists are expected to provide technical mentorship, establish best practices in MLOps and data CI/CD, and collaborate closely with executive stakeholders, product managers, and engineering teams to align data science roadmaps with overarching company goals.

The typical skill set for these senior roles is both deep and broad. A strong advanced degree (MS or PhD) in a quantitative field like Computer Science, Statistics, or Applied Mathematics is commonly expected. Candidates must possess expert-level proficiency in programming languages such as Python and SQL, along with mastery of machine learning libraries and frameworks for everything from classical statistics to cutting-edge neural networks and, increasingly, Generative AI and LLMs. Beyond technical acumen, successful Staff Data Scientists demonstrate exceptional business acuity, with the ability to communicate complex findings to non-technical audiences and influence strategic decisions. They exhibit a proactive, hypothesis-driven mindset, excelling in problem-solving, project leadership, and navigating ambiguity to deliver results.

For seasoned data scientists seeking to leverage their expertise at a strategic level, Staff Data Scientist jobs offer a challenging and rewarding path to shape the future of data-driven enterprises. Explore opportunities where you can lead innovation, build production-grade AI systems, and drive tangible business value at scale.