Senior Data Scientist - Streaming Experimentation and Modeling - Netflix
- Data Scientist
- Data Analytics
Netflix is revolutionizing entertainment. We deliver over a billion hours of movies and TV shows per month to more than 75 million members globally. Our data-driven culture allows us to continuously innovate and provide the best experience for our members. We are at the forefront of using advanced mathematical models and algorithms on big data to personalize the experience that every member has, and our scientists and engineers are constantly looking for new ways to improve the state of the art. Netflix data science is a unique combination of big data, algorithms, and entertainment: where else do you get to work on big data and win fourteen Emmys (four for technical achievement), two Golden Globes, and earn back to back Oscar nominations!
Netflix maintains a relentless focus on experimentation in order to improve the experience for our members. The Streaming Science and Algorithms team partners with engineering teams to develop and test new approaches and algorithms to improve the streaming Quality of Experience (QoE). These algorithms have a direct impact on the viewing experience as they determine key aspects of the experience such as video quality, delay before playback starts, and ensuring an uninterrupted playback session.
In this role, you will have the opportunity to optimize the Netflix streaming experience by designing experiments to evaluate changes to our streaming-related algorithms, and use rigorous statistical modeling and analysis to discover critical insights that shape the product experience for millions of Netflix subscribers around the world. The streaming QoE space is still nascent and as part of our team, you will have the opportunity to do groundbreaking modeling and experimental work that will shape the industry.
- Partner closely with scientists and engineers to design, run, and analyze A/B and multivariate tests aimed at testing hypotheses and optimizing the streaming video experience.
- Develop causal inference methodology to analyze behavior in cases where A/B testing may not be possible.
- Analyze experimental data with statistical rigor. Ensure accurate interpretation by combining business acumen with detailed data knowledge and statistical expertise.
- Build statistical models to uncover insights or effect changes in the product.
- Support internal research into new methodologies for experimentation, as well as adapt existing methods such as Response Surface Methodology (RSM) to online A/B testing.
- Translate analytic insights into concrete, actionable recommendations for business or product improvement, and communicate these findings.
- Drive efforts to enable independent interpretation of results through education, improved tools, and data visualization.
- Innovation for the experimentation-based "consumer science" approach at Netflix.
- PhD degree in Statistics, Mathematics, Operations Research, Psychology, Sociology, Econometrics, or related field.
- 4+ years relevant experience with a proven track record of leveraging analytics and large amounts of data to drive significant business impact.
- Solid statistical knowledge and intuition, ideally utilized in experimentation and modeling.
- Strong algorithmic thinking and independent research ability.
- Passion for learning and innovating new methodologies at the intersection of statistics, applied math, and computer science.
- Exceptional interpersonal and communication skills coupled with strong business acumen. Must be able to translate business objectives into actionable analyses, and analytic results into actionable business and product recommendations.
- Impactful presentation skills, including the use of meaningful charts, graphs, or other data visualizations to convey information and results clearly and concisely.
- High-energy self-starter with a passion for your work, attention to detail, and a positive attitude.
- Proficiency in at least one statistical analysis tool such as R, SAS, etc.
- Above average capabilities with SQL.
- Experience with distributed databases and query languages such as Hive/Pig and/or general map reduce computing is a plus.
- Knowledge of common data structures and ability to write efficient code in at least one language is a plus.
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