At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. The Member Applied Research Data Science and Engineering team drives foundational research to advance the measurement and understanding of member value. We guide optimal product decision-making while balancing trade-offs, and connect on-the-ground needs from individual teams to holistic priorities and methods shared across the Netflix ecosystem. We are seeking a Senior Data Scientist with strong causal inference and experimentation experience to advance our understanding of member engagement with a growing variety of available content and new interaction types. In this role, you will drive foundational research, new metric development, and experimentation strategies that directly guide decision-making across the Netflix product. You’ll work in a highly collaborative and cross-domain environment with other data scientists, data and analytics engineers, and business teams to accelerate our measurement capabilities and influence our strategy. In this role, you will: - Drive product innovation through robust measurement strategies across experimentation, modeling, and analytics to shape how our members experience a variety of content types. - Establish strong partnerships with stakeholders to ladder local developments into a holistic measurement approach. - Contribute new methodologies to our causal inference tooling. - Develop experimentation and measurement frameworks to increase the velocity of investments and aid complex decision-making. To be successful in this role, you have: - Advanced degree in Statistics, Mathematics, Computer Science, Economics or related quantitative field. - 5+ years of relevant experience focused on building and delivering real-world machine learning models with demonstrated impact. - Strong statistical knowledge and intuition - ideally utilized in experimentation or other product analytics settings. - Strong Quantitative Programming skills in a language such as Python. - Exceptional oral and written communication skills. - Passion for driving product vision and innovation strategy by leveraging a broad set of techniques and building strong partnership with stakeholders. - Strong product sense to balance between addressing stakeholder or test-specific needs and investing in scalable solutions to serve general use cases. - Ability to work independently and drive your own projects. - Embody Netflix values while bringing a new perspective to continue to improve our culture. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $372,000.00 - $600,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

• This position is responsible for building predictive, forecasting, and optimization models for the system of hospitals at OHSU health. • Designs models necessary to forecast capacity issues facing the institution. • Providing technical leadership for defining and developing advanced analytics products. • Use methods from statistics (regression, survival modeling), econometrics (time series), and AI modeling (LLM or multi-modal). • Develop code that meets standards for reliability and scalability. • Output from the model should be provided in various forms to allow other users across the institution to use them. • Delivering business intelligence products under required timelines and quality standards. • Work with ETL engineers to ensure efficient use of data. • Creating and maintaining a dashboard tool for visualizing and interacting with models. • Analyzing present and future data needs of customers and makes recommendations on options and alternatives for implementing applications, systems, or clinical/operational workflows and processes. • Configuration of output for use in dashboards, databases or other tabular forms. • Assists customers with the development of test plans and testing schedules for new systems and applications. • Contributing to the design of analytic, application, or workflow specifications for the most complex and critical OHSU systems and applications. • Ensuring data integrity and validity of models and systems. • Designs, develops and documents new applications and systems or clinical/operational workflows. • Design data reporting to make modeling results available to customers and other analysts at the institution. • Works with vendors, other technical staff and customers to design, develop, test and implement interfaces between systems. • Will fully understand and utilize the System Development Life Cycle (SDLC) process and procedures at OHSU. • Will manage projects by creating timelines, identifying risks and milestones, and providing status reporting to others as defined. • Assumes project management responsibilities for small projects or sub-projects within a larger project.

• Lead the design and implementation of causal inference frameworks (e.g., uplift modeling, DML, IVs, DiD, synthetic control) to measure true incremental impact across personalization, marketing, and lifecycle interventions • Establish and standardize methodologies for incrementality, experimentation, and measurement across channels and product surfaces • Build and scale LTV models (user-level and cohort-based), including churn-adjusted and horizon-specific approaches, for real-time decisioning • Develop and deploy personalization models that influence ranking, offer selection, content sequencing, and monetization strategies at the moment of user intent • Ship production-grade machine learning models that directly drive revenue outcomes, including marketplace optimization, partner routing, and budget allocation • Translate predictive outputs (e.g., conversion propensity, incremental CPA, expected LTV) into decision-ready signals for real-time systems • Partner with Data Engineering and Platform teams to define data instrumentation, feature stores (batch and streaming), and model monitoring frameworks (drift, bias, stability) • Influence architectural decisions across modern data and ML platforms (e.g., Snowflake, Databricks, Spark, real-time inference systems) • Provide technical leadership across teams by setting best practices for experimentation, modeling, code quality, and reproducibility • Mentor and develop senior and mid-level data scientists, raising the overall technical bar across the organization • Communicate complex analytical insights and trade-offs to executive stakeholders, translating findings into actionable business strategies • Shape long-term strategy for personalization, experimentation, and AI-driven growth at NerdWallet

• Drive GTM with Data • Build frameworks to identify and prioritize opportunities • Develop scoring approaches to guide GTM focus • Translate on-chain activity into clear, actionable insights • Support GTM decision-making with data • Support Sales Execution • Embed into sales workflows and engagements • Develop bespoke data narratives to strengthen pitches • Support live deals with relevant insights • Use data to differentiate in competitive opportunities • Expand Data Foundations • Build on existing data foundations to support GTM needs • Identify gaps in available data and work with data teams to address them • Ensure outputs are clear and usable for GTM teams • Translate Data into Action • Move from raw data to clear points of view • Deliver actionable recommendations, not just analysis • Connect on-chain signals with business context