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Yahoo
United States of America; US - United States of America
Source: Yahoo careers · View original posting
From Yahoo's posting. “We” and “our” refer to the employer.
Yahoo Mail is the ultimate consumer inbox with hundreds of millions of users. It’s the best way to access your email and stay organized from a computer, phone or tablet. With its beautiful design and lightning fast speed, Yahoo Mail makes reading, organizing, and sending emails easier than ever.
As part of Yahoo Mail - Data Science & Analytics, our team is the driving force behind experimental analysis, data science and business intelligence for Yahoo Mail. We thrive on data and insights to craft outstanding product experiences. Our commitment is towards providing data-driven guidance that fuels user growth and product innovation, maintaining high-quality data standards, and devising insightful A/B tests and advanced analyses.
Position Overview
As a Principal,, Data Scientist for Yahoo Mail, you will collaborate with product, design and engineering to enhance user growth strategies through product innovation. Your focus will be on designing and leading strategic research projects, utilizing your expertise in experimentation design, analytics, and AI-powered analytical approaches.
Who you are
A seasoned data science professional with a track record of solving complex business problems in digital media, product, or commerce environments.
Experienced in agile, iterative, and fast-paced experimentation environments, managing multiple projects within a matrixed team.
An effective communicator who presents insights to both technical and non-technical stakeholders with clarity and rationale.
Expertise in data querying languages (e.g., SQL) and scripting languages (e.g., Python).
Experience with big data technologies, including BigQuery, Hive, Hadoop, and Spark.
Proficiency in visualization tools such as Tableau and/or Looker and third-party tools (e.g., Comscore, SimilarWeb, Data AI).
Hands-on experience with Experimentation Frameworks for A/B Testing and Multivariate Testing.
Strong machine learning skills, covering cluster analysis, neural networks, and predictive modeling.
Utilization of statistical techniques, including correlation analysis, design of experimentation, regression methods, and time series analysis.
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