Senior Data Scientist - Identity

Live Ramp is shaping the future of responsible data collaboration between the world’s leading brands, retailers, financial services providers, and healthcare innovators. As consumers embrace new AI-driven experiences, the Live Ramp data collaboration network exponentially expands the breadth and accuracy of the data on which marketing AI capabilities operate, powering deeper customer insight and measurable performance on a global scale. Live Ramp is headquartered in San Francisco, California, with offices worldwide.

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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 data, and de-risk new product investments.

• Contribute high-quality, well-tested, and maintainable code, documentation, and dashboards that make your work reproducible, observable, and easy to operate.

• Mentor and support other data scientists and analysts through code reviews, design sessions, and sharing best practices.

• Build and evolve data science capabilities that sit at the heart of Live Ramp’s identity and data collaboration products, working closely with engineering teams across the company.

• Tackle a diverse portfolio of problems, from improving core matching and graph-based algorithms to powering customer-facing features for targeting, measurement, and analytics.

• Collaborate cross-functionally with product, engineering, customer success, and go-to-market teams to ship solutions that are technically sound, operationally scalable, and aligned with customer needs.

• Maintain a culture of experimentation and scientific rigor, using well-designed tests, strong baselines, and clear metrics to guide decisions.

• Invest in shared tooling, libraries, and best practices that raise the bar for how data science is done and operationalized across Live Ramp.

• MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field, or equivalent practical experience.

• 3+ years of experience designing, building, and deploying data science or machine learning solutions in a production environment.

• Proficiency in Python and SQL, along with experience using common data and ML libraries and frameworks (for example, pandas, Num Py, scikit-learn, or similar).

• Experience working with large datasets in a cloud environment and with modern data processing frameworks or warehouses (for example, Big Query).

• Demonstrated ability to independently frame ambiguous business or product questions as concrete, testable data science problems.

• Strong analytical and problem-solving skills, with a focus on clear measurement, experimentation, and data-informed decision-making.

• Excellent written and verbal communication skills, including the ability to present complex technical topics to both technical and non-technical audiences.

• A product-focused mindset and a strong bias…