Data Scientist
RokuNew York, New York$152k – $184kPosted 24 February 2026
Tech Stack
Job Description
<div class="content-intro"><h2 style="font-family: GothamBold,Helvetica,Arial,sans-serif; color: #662d91;">Teamwork makes the stream work.</h2>
<p> </p>
<h3 style="font-family: GothamBold,Helvetica,Arial,sans-serif;"><strong>Roku is changing how the world watches TV</strong></h3>
<p>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.</p>
<p>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.</p>
<p> </p></div><h3>About the team</h3>
<p>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.</p>
<p> </p>
<h3>About the role</h3>
<p>Roku is looking for a Data Scientist to join the Core Analytics team and provide support 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. </p>
<p>This role is more than analytics and is intentionally “business-forward”. 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. Familiarity with causal inference/experimentation is important; deep specialization is a plus but not required. This is a hybrid role with four days per week in the office, Monday through Thursday. The selected candidate will be based out of NYC. </p>
<p>For New York Only - The estimated annual salary for this position is between $152,000-$184,000 annually. </p>
<p>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. </p>
<p> </p>
<h3>What you'll be doing </h3>
<ul>
<li>Own end-to-end analyses: scope the question, define success metrics, pull data, analyze, synthesize, and deliver data-driven narratives. </li>
<li>Drive stakeholder alignment: clarify objectives, assumptions, tradeoffs, and decision points; ensure outputs are usable. </li>
<li>Build crisp storytelling presentations: create executive-ready readouts (slides, memos) with clear “so what / now what.” </li>
<li>Develop SQL and Python-based workflows: write and review SQL/Python code to create datasets, compute KPIs, and validate results; use Airflow to maintain and build new pipelines when needed. </li>
<li>Create reporting in Tableau/Looker: develop dashboards or recurring scorecards that make performance tracking easier and reduce ad-hoc churn. </li>
<li>Measurement causal thinking: apply or partner on quasi-experimental approaches (e.g., diff-in-diff, propensity matching, synthetic controls) with appropria ... (truncated, view full listing at source)
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