Senior Manager, Data Science Services

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:

• Lead a portfolio of data science services engagements for strategic customers, from scoping through delivery, ensuring projects meet agreed business outcomes, timelines, and quality standards.

• Translate client business objectives into rigorous analytical designs and experimentation frameworks that leverage LiveRamp’s identity, measurement, and data collaboration capabilities.

• Own executive‑level client relationships for your projects, including setting expectations, communicating results and tradeoffs, and influencing senior stakeholders using clear, data‑driven narratives.

• Partner closely with Sales, Customer Success, Product, and Engineering to design and package repeatable data science offerings that drive adoption and revenue for LiveRamp.

• Build and manage a high‑performing team of data scientists and analytics consultants through hiring, coaching, goal‑setting, and ongoing performance management.

• Establish and continuously improve delivery standards, best practices, code templates, and documentation for experimental design, modeling, and analytics on LiveRamp’s platform.

• Define and track key performance indicators for your portfolio (e.g., project margin, on‑time delivery, NPS/CSAT, incremental revenue delivered for clients) and use them to guide prioritization.

• Review and challenge analytical work products, ensuring statistical rigor, appropriate methodology selection, and clear articulation of assumptions, limitations, and business implications.

• Advocate for clients and delivery teams in internal roadmap discussions, translating emerging client use cases into product feedback and new service opportunities.

• Contribute to thought leadership by developing case studies, playbooks, and internal training that scale advanced analytics and experimentation skills across Global Services.

Your team will:

• Partner with enterprise customers to design and execute high‑impact data science initiatives that unlock the full value of LiveRamp’s platform—ranging from audience and media optimization to incrementality measurement, marketing mix and budget allocation, and advanced customer analytics.

• Operates as a cross‑functional, hands‑on delivery team that combines statistical and machine learning expertise with deep knowledge of identity, privacy‑centric data collaboration, and the adtech/martech ecosystem. Your team will work day‑to‑day in client data environments and LiveRamp‑connected ecosystems to clean, join, and activate large‑scale datasets.

• Own the end‑to‑end analytics lifecycle for services engagements: defining hypotheses and success metrics, building robust data pipelines, running models and experiments, synthesizing insights, and packaging recommendations into actionable roadmaps that customers can operationalize.

• Collaborate closely with other Global Services teams to turn successful bespoke projects into scalable accelerators, frameworks, and best practices that can be reused across accounts and regions.

About you:

• 8+ years of experience in data science, analytics, or applied statistics roles, with at least 3 years leading analytics or data science teams in a client‑facing or consulting environment.

• Proven track record of delivering measurable business impact through experimentation, predictive modeling, or advanced analytics in domains such as marketing, adtech, retail, financial services, or consumer technology.

• Strong proficiency with Python, PySpark for data science and exceptional SQL skills suitable for working with large, complex datasets.

• Strong knowledge of statistical modeling and machine learning techniques, especially regression, classification and time‑series analysis.

• Experience using modern data and analytics tools and frameworks (for example, Spark, dbt, Jupyter, or BI tools such as Looker or Tableau).

• Hands‑on experience designing and analyzing experiments (for example, A/B tests, holdout tests, or geo‑tests) and causal inference methods.

• Demonstrated ability to communicate complex technical concepts to non‑technical stakeholders through clear storytelling, data visualization, and structured recommendations.

• Experience managing multiple concurrent projects or programs, including scoping, estimation, resource planning, and risk management in a professional services or consulting context.

• Comfortable working with cloud‑based data and analytics environments and collaborating with technical stakeholders such as data engineers, solution architects, and product managers.

• Bachelor’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related discipline.

Preferred Skills:

• Experience in adtech, martech, or digital marketing analytics, including topics such as addressable media, identity resolution, attribution, or media measurement.

• Familiarity with customer data platforms, clean rooms, or data collaboration environments and the privacy and governance considerations that come with them.

• Prior experience at a consulting firm, agency, or professional services organization delivering data science or analytics projects to external clients.

• Background working with cross‑functional go‑to‑market teams and contributing to the design and pricing of data‑driven service offerings.

• Advanced degree (Master’s or PhD) in a quantitative discipline.

The approximate annual base compensation range is $181,000 to $263,000. 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.  Also Employee Stock Purchase Plan - 15% discount off purchase price of LiveRamp stock (U.S. LiveRampers)

• RampRemote: A comprehensive office equipment and ergonomics program—we provide you with equipment and tools to be your most productive self, no matter where you're located

LiveRamp is an affirmative action and equal opportunity employer (AA/EOE/W/M/Vet/Disabled) and does not discriminate in recruiting, hiring, training, promotion or other employment of associates or the awarding of subcontracts because of a person's race, color, sex, age, religion, national origin, protected veteran, disability, sexual orientation, gender identity, genetics or other protected status. Qualified applicants with arrest and conviction records will be considered for the position in accordance with the San Francisco Fair Chance Ordinance. 

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