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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Research Data Scientist - **Company:** DATA 206 LLC - **Location:** Boston, MA, United States (Remote available) - **Experience:** Expert - **Salary:** $330,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Information Engineering, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Data Streaming, Apache Spark, Scikit Learn, Xgboost, Build Tools - **Published:** July 17, 2026 - **Apply:** https://www.dice.com/job-detail/174328bb-0024-4a9c-9f2b-e352c38e33e3 ## About the Role * PhD in Economics, Econometrics, Statistics, or a closely related quantitative field with a strong emphasis on causal inference * 10+ years of experience applying causal inference and machine learning methods to real-world problems, with a demonstrated track record of measurable impact * Deep expertise in observational causal methods such as propensity score matching, Double Machine Learning, doubly robust estimation, instrumental variables, and difference-in-differences * Experience building reusable causal inference tools or platforms beyond one-off analyses * Proficiency with Spark, Ray, SQL, Python, and ML frameworks such as scikit-learn, XGBoost, and LightGBM * Experience with terabyte- or petabyte-scale datasets in distributed computing environments * Strong communication skills with the ability to translate econometric findings into clear business recommendations * Technology industry experience; connected TV, streaming, or advertising experience is a plus #LI-SB5 What's Roku's approach to hybrid working? ## Description 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 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., * Design, build, and productionize a causal inference platform that standardizes how Roku measures the incremental impact of customer actions and business decisions * Research and implement causal estimation methods, including heterogeneous treatment effects, tailored to Roku's data and business questions * Build long-term outcome frameworks that enable impact projection from limited observation windows * Develop diagnostic and validation standards at scale to ensure credibility of causal estimates * Leverage AI to create counterfactual scenarios and build tools that help users run, understand, and act on causal estimates correctly * Work cross-functionally with Data Engineering, Product Management, and Core Analytics to translate business questions into well-defined causal problems and deploy production-ready solutions * Contribute to the technical vision of the Data Science team and the broader research agenda across causal inference, predictive modeling, and experimentation, Roku fosters an inclusive and collaborative environment where teams generally work in the office Monday through Thursday. 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