Senior Data Scientist - Identity

About the role

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.

Responsibilities

• 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.

Requirements

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, NumPy, scikit-learn, or similar).

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

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 toward iterative execution—you are comfortable moving from idea to prototype to production quickly while incorporating feedback.

Preferred Skills

• Experience with embeddings, representation learning, or large-scale similarity and ranking systems.
• Experience with approximate nearest neighbor search, vector databases, or other large-scale vector search technologies.
• Experience designing and implementing robust evaluation frameworks and monitoring for ML systems, including offline/online metric alignment and experimentation.
• Experience with Google Cloud Platform and its data and ML ecosystem (for example, BigQuery, Dataflow, Vertex AI, or similar).
• Familiarity with privacy-preserving data practices and governance, and interest in responsible and ethical use of data.
• Experience with identity, entity resolution, or graph-based modeling in advertising, marketing, or adjacent domains.

Skills

• Python
• SQL
• Large-scale data processing frameworks (e.g., BigQuery)
• Machine learning and statistical modeling
• Data analysis and transformation
• Cloud environments
• Experimentation and evaluation frameworks
• Google Cloud Platform
• Privacy-preserving data practices
• Identity, entity resolution, or graph-based modeling

Benefits

The approximate annual base compensation range is $130,000 to $196,500. The actual offer, reflecting the total compensation package and benefits, will be determined by a number of factors including the applicant's experience, knowledge, skills, and abilities, geography, as well as internal equity among our team.

People: Work with talented, collaborative, and friendly people who love what they do.

Fun: We host in-person and virtual events such as game nights, happy hours, camping trips, and sports leagues.

Work/Life Harmony: Flexible paid time off, paid holidays, options for working from home, and paid parental leave.

Comprehensive Benefits Package: LiveRamp offers a comprehensive benefits package designed to help you be your best self in your personal and professional lives. Our benefits package offers medical, dental, vision, life and disability, an employee assistance program, voluntary benefits as well as perks programs for your healthy lifestyle, career growth and more.

Savings: Our 401K matching plan—1:1 match up to 6% of salary—helps you plan ahead.

More About Us: LiveRamp’s mission is to connect data in ways that matter, and doing so starts with our people. We know that inspired teams enlist people from a blend of backgrounds and experiences. And we know that individuals do their best when they not only bring their full selves to work but feel like they truly belong. Connecting LiveRampers to new ideas and one another is one of our guiding principles—one that informs how we hire, train, and grow our global team across nine countries and four continents.