LiveRamp

Senior Data Scientist

LiveRamp • $130K — $196K *
Little Rock, AR 72204In-Person
Enterprise Technology
Less than 5 years of experience
Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • MS or PhD in a quantitative field or equivalent practical experience.
  • 3+ years of experience in production data science or machine learning solutions.
  • Proficiency in Python and SQL; familiar with data libraries like pandas and scikit-learn.
  • Experience with large datasets in cloud environments and modern data processing tools.
  • Strong analytical skills for framing business problems as testable data science projects.
  • Excellent communication skills for both technical and non-technical audiences.
  • Product-focused mindset with a bias for rapid execution and iterative development.

Responsibilities

  • Design, implement, and optimize machine learning models for identity and measurement.
  • Analyze messy datasets to extract insights and improve model performance.
  • Manage end-to-end data science workflows in collaboration with Engineering.
  • Translate technical analysis into actionable insights for stakeholders.
  • Define success metrics and evaluate business impact of initiatives.
  • Collaborate with Product Management to create data solutions for customer needs.
  • Mentor junior team members through code reviews and best practice guidance.

Benefits

  • Collaborative and friendly team environment.
  • Engaging social events including game nights and sports leagues.
  • Flexible paid time off and work-from-home options.
  • Extensive medical, dental, vision, and wellness programs.
  • 401K matching plan to support retirement savings.
Full Job Description
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.
Your team will:
  • Build and evolve data science capabilities that sit at the heart of LiveRamp'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 LiveRamp.
About you:
  • 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.
    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.
Benefits:
  • 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.

About LiveRamp

LiveRamp is a data connectivity platform that enables the safe and effective use of data. LiveRamp connects data owners and providers with the people-based marketing platforms that need that data for targeting and measurement. LiveRamp is the largest onboarding company in the world, and its technology serves as the bridge between offline customer data and online advertising.
Learn more about LiveRamp
Size
1,400 employees
Market Cap
$1.5 billion
Industry
Information Technology
Net Income
-$61.5 million
Founded
1969
5 Year Trend
+24.8%
Revenue
$429.5 million
NASDAQ
RAMP
* Ladders Estimates

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