Director, Data Science

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.

Are you passionate about using data to drive strategic business impact? We are seeking an experienced and inspiring leader to guide our data science team and shape the direction of our data-driven initiatives. As the Director, Data Science, you will be responsible for building and mentoring a world-class team, developing cutting-edge data science capabilities, and partnering with cross-functional stakeholders to realize the company's vision. This high-impact, high-visibility position reports to the VP of Engineering and will have strong exposure to the leadership team.

You are a dynamic leader with a deep background in data science, machine learning, and analytics, and have experience leading high-performing teams that deliver measurable business value. You know how to partner effectively across functions, set a multi-year data strategy, and foster a culture of technical excellence, experimentation, accountability, and inclusion. You are comfortable going deep technically while also setting a compelling vision for your team. You embrace modern data and machine learning best practices and can balance hands-on leadership with strategic thinking.

As Director, Data Science, you will oversee the design and implementation of AI/ML solutions across the organization, champion a culture of data-informed decision making, and represent the data science function both internally and externally. You will collaborate closely with Engineering, Product, and Business leaders to drive impact at scale.

Key responsibilities:

• Lead the architecture and design of distributed systems, high-performance data processing pipelines—including large-scale Spark jobs—and complex system integrations.

• Develop and maintain architectural standards and best practices for distributed computing and scalable data platforms (batch and streaming).

• Serve as a technical leader and subject matter expert on distributed systems, Spark, cloud computing, and data processing technologies.

• Drive the technical roadmap and strategy in partnership with product, engineering, and business stakeholders.

• Conduct architecture and code reviews, ensuring reliability, scalability, security, and operational excellence across the platform.

• Evaluate and prototype new technologies, tools, and patterns to advance system capabilities and efficiency.

• Mentor engineers and guide teams on distributed computing paradigms, system design, and implementation best practices.

• Collaborate with cross-functional teams to translate business and product requirements into robust, scalable architecture.

• Ensure the integrity, performance, and scalability of mission-critical systems, championing monitoring, automation, and incident response best practices.

• Represent the company externally as a thought leader in distributed computing and big data architecture.

• Bachelor’s or Master’s in Computer Science or Engineering (PhD a plus).

• 10+ years of hands-on experience in software engineering, architecture, or similar technical roles, with a focus on distributed computing and large data systems.

• Extensive experience designing, implementing, and optimizing production-grade Spark applications and distributed data processing solutions.

• Proven ability to solve complex technical problems at scale, with a robust approach to reliability, performance, and security.

• Skilled in architectural review, technical leadership, and cross-team collaboration.

• Excellent verbal and written communication skills, including an ability to articulate complex technical decisions and solutions to both technical and non-technical audiences.

• Extensive experience in developing and deploying machine learning models in production, including model training, hyperparameter tuning, and evaluation using frameworks like TensorFlow, PyTorch, and scikit-learn.

• Proficient in building ML pipelines, automated retraining workflows, and feature stores with tools like Kubeflow, MLflow, TFX, Airflow, and SageMaker Pipelines.

• Solid understanding of MLOps principles—versioning, reproducibility, CI/CD for ML, model monitoring, drift detection, and governance.

• Experience with experimentation platforms, A/B testing frameworks, and applying statistical rigor to evaluate model performance in real-world conditions.

• Knowledge of responsible AI practices, including fairness, explainability (e.g., SHAP, LIME), and regulatory compliance (e.g., GDPR, HIPAA).

• Highly ethical, detail-oriented, accountable, and committed to fostering technical excellence.

• Experience in high-growth, dynamic technology companies in the US market.

• Previous experience as a data scientist for large-scale distributed systems.

• Contributions to open-source projects or publications in distributed computing.

• Experience working in global or geographically distributed engineering teams.

• Ability to influence and build alignment without direct authority in a matrixed environment.

The approximate annual base compensation range is $244,000 to $280,000. 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. 

California residents: Please see our California Personnel Privacy Policy for more information regarding how we collect, use, and disclose the personal information you provide during the job application process.

To all recruitment agencies: LiveRamp does not accept agency resumes. Please do not forward resumes to our jobs alias, LiveRamp employees or any other company location. LiveRamp is not responsible for any fees related to unsolicited resumes.