Senior Data Scientist

Roku•New York City, NY

2d•$157,000 - $187,000•Hybrid

About The Position

Teamwork makes the stream work. Roku is changing how the world watches TV Roku is the #1 TV streaming platform in the U.S., Canada, and Mexico, and we've set our sights on powering every television in the world. Roku pioneered streaming to the TV. Our mission is to be the TV streaming platform that connects the entire TV ecosystem. We connect consumers to the content they love, enable content publishers to build and monetize large audiences, and provide advertisers unique capabilities to engage consumers. From your first day at Roku, you'll make a valuable - and valued - contribution. We're a fast-growing public company where no one is a bystander. We offer you the opportunity to delight millions of TV streamers around the world while gaining meaningful experience across a variety of disciplines. About the team The Core Analytics Team is a centralized function dedicated to providing data-driven insights to drive business and product success. We work closely with our Product, Engineering, and Marketing teams to deliver exceptional experiences to our customers while maximizing the value proposition for the business. About the role Roku is looking for a Senior Data Scientist to join the Core Analytics team and drive data-driven insights for our Customer Intelligence function, part of the broader Planning & Optimization team. Together, we answer high-impact business questions from senior leaders with clear, decision-ready insights. You’ll work on customer analytics that directly shape how Roku grows engagement, retention and monetization across the streaming ecosystem, with visibility to cross-functional leaders and meaningful ownership over high-impact questions. This role is designed to operate at the intersection of analytics and business strategy. We're looking for someone who can translate customer behavior into metrics and narratives which can help define our customer strategy, and/or measure the impact of initiatives on customer behavior. You’ll be expected to translate ambiguous stakeholder needs into strong analytical narratives and executive-ready deliverables. A core part of this work involves measuring incremental impact and distinguishing true effects from noise. Familiarity with causal inference and experimentation is important; deep specialization is a plus but not required. For New York Only - The estimated annual salary for this position is between $157,000 to $187,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location.  This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

Requirements

5+ years of experience in data science or advanced analytics roles driving measurable business impact.
Demonstrated ownership of ambiguous, high-visibility analytical problems.
Experience building reusable measurement frameworks or scalable impact evaluation methodologies.
Strong proficiency in Excel, SQL and Python for data analysis and visualization.
Experience building reusable analytical code and productionizing workflows (e.g., Airflow or similar tools).
Hands-on experience with Tableau or Looker for reporting.
Ability to communicate complex findings clearly to both technical and executive audiences.

Responsibilities

End-to-end Advanced Analytics: lead the design, execution, and delivery of complex analyses, leveraging advanced analytics to understand customer behavior, predict churn, identify growth opportunities, and measure the incrementally of initiatives.
Technical Execution & Automation: develop, optimize, and maintain scalable SQL and Python-based data pipelines and analytical workflows. Write production-quality code to create datasets, compute KPIs, validate results, and build predictive/causal models when needed. Partner with Data Engineering to enhance data quality, metric consistency, and pipeline reliability, including leveraging tools like Airflow.
Dashboarding & Reporting: create and maintain Tableau/Looker dashboards and recurring scorecards that empower business teams with self-service insights, reducing ad-hoc requests and enabling continuous performance monitoring.
Raise Analytical Bar: champion best practices in statistical rigor, bias awareness, and data governance. Continuously explore new methodologies and tools to elevate the team's analytical capabilities.
Business-Oriented Storytelling & Communication: craft compelling, executive-ready narratives and presentations (slides, memos) that clearly articulate complex analytical findings, strategic implications, and actionable recommendations to both technical and non-technical audiences, influencing decision-makers across the organization.
Stakeholder Partnership: clarify objectives, assumptions, tradeoffs, and decision points; ensure outputs are usable.