Senior Data Scientist - Identity

LiveRamp, Inc.•Seattle, WA

22d•$130,000 - $196,500

About The Position

LiveRamp is hiring a Senior Data Scientist to develop and operate production-grade data science and machine learning capabilities for identity, entity resolution, measurement, and data collaboration products. The role works closely with Engineering and cross-functional partners to turn customer and business needs into measurable, scalable solutions. The position owns work from problem framing and data exploration through modeling, deployment, monitoring, and ongoing improvement, while contributing to shared data science tools, practices, and team development.

Requirements

MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related quantitative field, or equivalent practical experience.
At least 3 years of experience designing, building, and deploying data science or machine learning solutions in a production environment.
Proficiency in Python and SQL, and experience with common data and machine learning libraries or frameworks such as pandas, NumPy, and scikit-learn, or similar.
Experience working with large datasets in a cloud environment and modern data processing frameworks or warehouses, such as BigQuery.
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 measurement, experimentation, and data-informed decision-making.
Excellent written and verbal communication skills, including explaining complex technical topics to technical and non-technical audiences.
Product-focused mindset and bias toward iterative execution, with comfort moving from idea to prototype to production while incorporating feedback.

Nice To Haves

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 machine learning systems, including offline/online metric alignment and experimentation.
Experience with Google Cloud Platform and its data and machine learning ecosystem, such as BigQuery, Dataflow, or Vertex AI.
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.

Responsibilities

Design, implement, and iterate on production-grade machine learning and statistical models for identity, entity resolution, and measurement capabilities.
Analyze and transform large-scale, high-dimensional, and messy datasets; uncover actionable insights, engineer 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 collaboration with Engineering.
Communicate technical concepts and analyses as clear recommendations for product, engineering, and go-to-market stakeholders.
Define and track success metrics, develop experimentation and evaluation frameworks, and run tests to quantify business impact.
Partner with Product Management to scope data-driven solutions, validate hypotheses, and de-risk product investments.
Produce well-tested, maintainable code, documentation, and dashboards that make work reproducible, observable, and operable.
Mentor and support data scientists and analysts through code reviews, design sessions, and sharing best practices.
Collaborate with engineering, product, customer success, and go-to-market teams to build and ship scalable solutions aligned with customer needs.
Contribute to shared tooling, libraries, and practices that improve how data science is conducted and operationalized.