Senior Research Data Scientist

We need to output HTML fragment with sections: About the team, About the role, What you'll be doing, We're excited if you have, What's Roku's approach to hybrid working?, What are some of the benefits?, Accommodations?, What should I know about Roku's culture? Also include Pay and Schedule sections only if present. Pay: there is salary range for California only. That is specific: "For California Only - The estimated annual base salary for this position is between $203,800 - $323,700." So we should include a Pay section with that info. Schedule: hybrid working description includes schedule: Monday-Thursday office, Fridays flexible remote. That's schedule info. So include Schedule section. We must not repeat job title. No Job ID. Remove boilerplate like EEO, legal, application instructions, etc. Also remove duplicated lines. Keep all substantive info. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to decide which content goes into lists. Sections: - About the team: prose paragraph(s). Could be multiple paragraphs but we can combine into

  . - About the role: prose. - What you'll be doing: list of duties. Use

  • . - We're excited if you have: list of qualifications/requirements. Use
    • . - What's Roku's approach to hybrid working?: could be prose or maybe list? It's description. Use

      . - What are some of the benefits?: list of benefits. Use

      • . - Accommodations: prose. - What should I know about Roku's culture?: prose. - Pay: maybe

        with salary range. - Schedule: maybe

        with hybrid schedule. We must not create sections with filler. All sections have content. We must not include duplicated lines. Ensure we don't repeat same sentences. Let's extract content. Original text: "Teamwork makes the stream work. Roku is changing how the world watches TVRoku 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 teamOur Data Science team is a high-impact research team actively shaping the future of TV, using Big Data to build and enhance the user experience on the Roku streaming platform. Our production-ready machine learning models and statistical solutions optimize the user experience across all of Roku's core business models and products, and our scientists engage closely with business, product, and engineering leaders to make material and measurable impacts on the success and growth of the platform. About the roleAs a Senior Research Data Scientist on Roku's Data Science team, you will lead the development of a best-in-class causal inference platform that measures and optimizes the true incremental impact of customer actions, product features, and business interventions on long-term outcomes. Partnering with the Customer Growth organization, you will build the methods and systems that enable Roku to make high-confidence decisions from observational data when randomized experiments are not feasible.You will own the full lifecycle of causal measurement—from gathering business requirements and defining estimation approaches, to partnering with Engineering to productionize scalable causal pipelines and communicating findings to senior leadership. Your work will directly inform growth, retention, and monetization strategy across the platform, making this role ideal for an applied economist or econometrician who excels at the intersection of rigorous research and production engineering. This is someone equally comfortable deriving identification strategies and building estimators on terabyte-scale data.For California Only - The estimated annual base salary for this position is between $203,800 - $323,700. 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. What you'll be doingDesign, build, and productionize a causal inference platform that standardizes how Roku measures the incremental impact of customer actions and business decisionsResearch and implement causal estimation methods, including heterogeneous treatment effects, tailored to Roku's data and business questionsBuild long-term outcome frameworks that enable impact projection from limited observation windowsDevelop diagnostic and validation standards at scale to ensure credibility of causal estimatesLeverage AI to create counterfactual scenarios and build tools that help users run, understand, and act on causal estimates correctlyWork cross-functionally with Data Engineering, Product Management, and Core Analytics to translate business questions into well-defined causal problems and deploy production-ready solutionsContribute to the technical vision of the Data Science team and the broader research agenda across causal inference, predictive modeling, and experimentation We're excited if you havePhD in Economics, Econometrics, Statistics, or a closely related quantitative field with a strong emphasis on causal inference10+ years of experience applying causal inference and machine learning methods to real-world problems, with a demonstrated track record of measurable impactDeep expertise in observational causal methods such as propensity score matching, Double Machine Learning, doubly robust estimation, instrumental variables, and difference-in-differencesExperience building reusable causal inference tools or platforms beyond one-off analysesProficiency with Spark, Ray, SQL, Python, and ML frameworks such as scikit-learn, XGBoost, and LightGBMExperience with terabyte- or petabyte-scale datasets in distributed computing environmentsStrong communication skills with the ability to translate econometric findings into clear business recommendationsTechnology industry experience; connected TV, streaming, or advertising experience is a plus What's Roku's approach to hybrid working?Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. Fridays are generally flexible for remote work, except for employees whose specific roles or assigned office location require five days' a week attendance. What are some of the benefits?Roku is committed to offering a diverse range of benefits as part of our compensation package to support our employees and their families. Our comprehensive benefits include global access to mental health and financial wellness support and resources. Local benefits include statutory and voluntary benefits which may include healthcare (medical, dental, and vision), life, accident, disability, commuter, and retirement options (401(k)/pension). Employees are supported in taking time off, in accordance with local leave policies and other personal needs to support their evolving work and life needs. It's important to note that not every benefit is available in all locations or for every role. For details specific to your location, please consult with your recruiter. AccommodationsRoku welcomes applicants of all backgrounds and provides reasonable accommodations and adjustments in accordance with applicable law. If you require reasonable accommodation at any point in the hiring process, please direct your inquiries to EmployeeRelations@Roku.com. What should I know about Roku's culture?Roku is a great place for people who want to work in a fast-paced environment where everyone is focused on the company's success rather than their own. We try to surround ourselves with people who are great at their jobs, who are easy to work with, and who keep their egos in check. We appreciate a sense of humor. We believe a fewer number of very talented folks can do more for less cost than a larger number of less talented teams. We're independent thinkers with big ideas who act boldly, move fast and accomplish extraordinary things through collaboration and trust. In short, at Roku you'll be part of a company that's changing how the world watches TV. We have a unique culture that we are proud of. We think of ourselves primarily as problem-solvers, which itself is a two-part idea. We come up with the solution, but the solution isn't real until it is built and delivered to the customer. That penchant for action gives us a pragmatic approach to innovation, one that has served us well since 2002. To learn more about Roku, our global footprint, and how we've grown, visit https://www.weareroku.com/factsheet.By providing your information, you acknowledge that you want Roku to contact you about job roles, that you have read Roku's Applicant Privacy Notice, and understand that Roku will use your information as described in that notice. If you do not wish to receive any communications from Roku regarding this role or similar roles in the future, you may unsubscribe at any time by emailing WorkforcePrivacy@Roku.com." We need to remove boilerplate: the privacy notice lines at end, also maybe the "To learn more about Roku..." line? That's not boilerplate? It's a link to factsheet; could be considered extra but it's substantive? It's a link for more info; maybe we can keep? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The privacy notice and unsubscribe instructions are application instructions/legal; remove them. The "To learn more about Roku..." maybe not required but could be considered navigation? It's a link to factsheet; might be considered extra but not explicitly prohibited. Safer to remove it as it's not core job description. Also remove the initial fluff before About the team? The first paragraph about Roku mission etc. That's substantive? It's about company mission; could be considered part of About the team? But we have About the team section already. The initial fluff could be considered part of About the team? It repeats some of that. Might be considered duplicated. Safer to keep only the sections as headings and their content. The content before About the team is generic company overview; could be omitted as not under a heading. The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

        or drop it." It doesn't say we must include company overview. It says preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep the company overview if it's substantive. However it's not under a heading; we could put it into a

        before the first heading? But we must not create a heading for it. The instruction: "use

        for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid having prose outside headings. So we can include a leading

        with the company overview. However the overview includes some duplicated content that appears later in About the team. Might be considered duplicated. But we can keep it; but better to avoid duplication. The instruction: "Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions." So we should remove duplicated lines. The company overview duplicates some of About the team content. So we should drop it to avoid duplication. So start directly with About the team heading. Thus output:

        About the team

        Our Data Science team is a high-impact research team actively shaping the future of TV, using Big Data to build and enhance the user experience on the Roku streaming platform. Our production-ready machine learning models and statistical solutions optimize the user experience across all of Roku's core business models and products, and our scientists engage closely with business, product, and engineering leaders to make material and measurable impacts on the success and growth of the platform.

        About the role

        As a Senior Research Data Scientist on Roku's Data Science team, you will lead the development of a best-in-class causal inference platform that measures and optimizes the true incremental impact of customer actions, product features, and business interventions on long-term outcomes. Partnering with the Customer Growth organization, you will build the methods and systems that enable