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Data Scientist, Product, Googler Technology and Engineering

Global technology company that provides internet-related services and products.
Data
Mid-Level Software Engineer
In-Person
5,000+ Employees
5+ years of experience
AI · Enterprise SaaS
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Description For Data Scientist, Product, Googler Technology and Engineering

Google is seeking a Data Scientist to join their Googler Technology and Engineering team in Hyderabad. This role combines technical expertise in machine learning and data analysis with business impact. The ideal candidate will work on the full ML lifecycle, from ideation to production, focusing on solving enterprise support challenges. You'll be responsible for developing KPIs, creating and implementing statistical models, and providing strategic insights to drive decision-making across the organization. This position offers the opportunity to work with Google's vast data resources and impact its billion-plus user base. The role requires both technical prowess in data science and the ability to communicate insights effectively to stakeholders. Working at Google provides exposure to cutting-edge technology and the chance to solve complex problems at scale, while being part of a company known for innovation and technical excellence.

Last updated a month ago

Responsibilities For Data Scientist, Product, Googler Technology and Engineering

  • Provide leadership through proactive contributions and use insights and analytics to drive decisions
  • Work on problem definition, metrics development, data extraction and manipulation, visualization
  • Define and report Key Performance Indicators (KPIs) and launch impact
  • Design and develop machine learning models to solve problems within Enterprise Support space
  • Review analysis and business cases conducted by others to provide feedback

Requirements For Data Scientist, Product, Googler Technology and Engineering

Python
  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field
  • 5 years of work experience with analysis applications and coding (Python, R, SQL) (or 2 years work experience with a Master's degree)
  • Experience with the full Machine Learning product lifecycle
  • Experience applying Machine Learning and advanced analytics solutions to enterprise operations teams

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