Data Scientist, Analytics
SundayyAbout The Company
LiveRamp is a leading data collaboration platform that empowers the world's most innovative companies to harness the power of data responsibly and effectively. Renowned for its commitment to consumer privacy, data ethics, and foundational identity, LiveRamp sets new standards in building a connected customer view with unparalleled clarity and context, all while safeguarding brand and consumer trust. The platform offers unparalleled flexibility, enabling organizations to collaborate across data silos, whether within their own infrastructure, with partners, or across a global network of top-tier collaborators. With a client base that includes iconic consumer brands, technology giants, financial institutions, retailers, and healthcare providers, LiveRamp helps these organizations deepen customer engagement, activate strategic partnerships, and maximize the value of first-party data—all while navigating the complex landscape of privacy regulations and compliance requirements.
About The Role
We are seeking a highly skilled Principal Data Scientist, Analytics to join our dynamic team as we expand our self-service analytics and data science capabilities. In this role, you will be instrumental in developing scalable data and analytics frameworks, designing intuitive tools, and delivering trusted insights directly to business teams. Your work will primarily support our Product and Engineering divisions, where you will collaborate closely with architects and data engineers to shape data models, pipelines, and analytics frameworks that underpin impactful dashboards and advanced predictive and prescriptive analytics. You will be responsible for creating user-centric tools that empower teams to explore data, derive insights, and make informed decisions using platforms such as BigQuery, AI agents, and Tableau. Your expertise will help establish best practices, enhance data literacy, and foster a data-driven culture across the organization.
Qualifications
We are proud to be an Equal Employment Opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or any other basis protected by federal, state, or local law.
LiveRamp is a leading data collaboration platform that empowers the world's most innovative companies to harness the power of data responsibly and effectively. Renowned for its commitment to consumer privacy, data ethics, and foundational identity, LiveRamp sets new standards in building a connected customer view with unparalleled clarity and context, all while safeguarding brand and consumer trust. The platform offers unparalleled flexibility, enabling organizations to collaborate across data silos, whether within their own infrastructure, with partners, or across a global network of top-tier collaborators. With a client base that includes iconic consumer brands, technology giants, financial institutions, retailers, and healthcare providers, LiveRamp helps these organizations deepen customer engagement, activate strategic partnerships, and maximize the value of first-party data—all while navigating the complex landscape of privacy regulations and compliance requirements.
About The Role
We are seeking a highly skilled Principal Data Scientist, Analytics to join our dynamic team as we expand our self-service analytics and data science capabilities. In this role, you will be instrumental in developing scalable data and analytics frameworks, designing intuitive tools, and delivering trusted insights directly to business teams. Your work will primarily support our Product and Engineering divisions, where you will collaborate closely with architects and data engineers to shape data models, pipelines, and analytics frameworks that underpin impactful dashboards and advanced predictive and prescriptive analytics. You will be responsible for creating user-centric tools that empower teams to explore data, derive insights, and make informed decisions using platforms such as BigQuery, AI agents, and Tableau. Your expertise will help establish best practices, enhance data literacy, and foster a data-driven culture across the organization.
Qualifications
- MS or PhD in Computer Science, Statistics, Mathematics, or a related field.
- 10+ years of experience in Data Science and Analytics, with a proven track record of delivering high-impact product insights and scalable statistical models.
- Expert-level proficiency in Python and SQL, with extensive experience working with large datasets in cloud environments such as BigQuery.
- Hands-on experience building complex data science models and leveraging large language models (LLMs).
- Demonstrated ability to design and scale AI-powered analytics solutions and architect modern data science stacks.
- Deep understanding of Product Analytics metrics and concepts, especially within SaaS or platform environments.
- Strong business acumen with the ability to translate ambiguous questions into concrete technical solutions and articulate business value to non-technical stakeholders.
- Experience collaborating with data engineers and working with data modeling frameworks like dbt.
- Commitment to analytical rigor, reproducibility, and best practices in data science workflows.
- Proven leadership in mentoring analysts and data scientists, fostering analytics excellence across teams.
- Design, develop, and validate reusable, self-service metrics, dashboards, skills, agents, and analytical products tailored to business needs, enabling teams to answer complex questions independently.
- Partner with Product and Engineering teams to align analytics initiatives with strategic goals and embed decision logic within product lifecycle processes.
- Create semantic layers, metric frameworks, and analytical abstractions that support AI-assisted insights and natural language querying capabilities.
- Develop sophisticated analytical models, conduct deep-dive analyses, and present findings to executive leadership to inform high-impact decisions.
- Ensure explainability, trustworthiness, and governance of AI-driven analytics experiences, maintaining high standards of transparency and compliance.
- Develop predictive, diagnostic, and causal models to optimize product adoption, engagement, retention, and monetization strategies.
- Translate ambiguous product questions into formal models and statistically rigorous analyses, supporting data-driven decision-making.
- Lead experimentation strategies, including A/B testing, quasi-experiments, and causal inference to validate hypotheses and inform product development.
- Collaborate with data engineering teams to build scalable data pipelines, model-ready datasets, and feature engineering workflows that support reproducible data science models.
- Validate models, establish analytical frameworks, review methodologies, and elevate the quality of product analytics and data science work across the organization.
- Partner with cross-functional teams to define and prioritize analytics roadmaps, ensuring alignment with organizational objectives.
- Mentor and lead efforts to evangelize best practices in analytics, data science, and AI within the organization, fostering a culture of continuous learning and innovation.
- Opportunity to work with talented, collaborative, and passionate professionals dedicated to innovation.
- Participation in engaging in-person and virtual events such as game nights, happy hours, camping trips, and sports leagues.
- Flexible work arrangements including paid time off, paid holidays, remote work options, and paid parental leave to support work/life harmony.
- Comprehensive benefits package including medical, dental, vision, life and disability insurance, employee assistance programs, and perks promoting a healthy lifestyle and career growth.
- Generous 401K matching plan (1:1 match up to 6% of salary) to help plan for the future.
We are proud to be an Equal Employment Opportunity employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or any other basis protected by federal, state, or local law.