LiveRamp

Senior Data Scientist

LiveRamp
US San Francisco, CA, US
Onsite 2026-07-02
Announced salary
$130,000 - $196,500
Low
$113K
Median
$149K
High
$196K
Market in San Francisco · BLS OEWS 2025
Estimated net pay
$7,697 - $11,031
/month · 29% withheld
after tax & contributions · Single, no dependents

Job description

**LiveRamp is the data collaboration platform of choice for the world’s most innovative companies. A groundbreaking leader in consumer privacy, data ethics, and foundational identity, LiveRamp is setting the new standard for building a connected customer view with unmatched clarity and context while protecting precious brand and consumer trust. LiveRamp offers complete flexibility to collaborate wherever data lives to support the widest range of data collaboration use cases—within organizations, between brands, and across its premier global network of top\-quality partners.** **Hundreds of global innovators, from iconic consumer brands and tech giants to banks, retailers, and healthcare leaders turn to LiveRamp to build enduring brand and business value by deepening customer engagement and loyalty, activating new partnerships, and maximizing the value of their first\-party data while staying on the forefront of rapidly evolving compliance and privacy requirements.** **You will:** * Design, implement, and iterate on production\-grade machine learning and statistical models that power core identity, entity resolution, and measurement capabilities. * Analyze and transform large\-scale, high\-dimensional, and often messy datasets to uncover actionable insights, engineer robust features, and improve model performance and stability. * Own end\-to\-end data science workflows—from problem framing, data exploration, and modeling through deployment, monitoring, and continuous improvement—in close collaboration with Engineering. * Translate complex technical concepts and analysis into clear recommendations and narratives for product, engineering, and go\-to\-market stakeholders to inform roadmaps and prioritization. * Define and track success metrics, build experimentation and evaluation frameworks, and tests to quantify the business impact of your work. * Partner with Product Management to scope data\-driven solutions that address customer needs, validate hypotheses with

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