Product Analyst

Product Analyst



Disney+ Hotstar is leading the way as the largest and smartest video platform in the country, reaching over 300 million users today. We have set a number of world records along the way – including for the highest concurrent viewership at 25.3 million during the ICC Cricket World Cup 2019. Disney+ Hotstar today is the one-stop destination for all your entertainment needs – from Live Sports, Indian and International Shows and Movies to all Disney content, including Pixar, Marvel, Star Wars, National Geographic and Disney+ Originals. We’re looking for the brightest minds to build the future of TV with us

About The Team

Hotstar is looking for smart and driven data analysts to join our product team and help drive the growth and success of the product. The candidate will need to have deep technical skills to complement their analytical experience The ideal candidate will be scrappy, independent, action oriented and excited about building data insights to influence product priorities

The pace of our growth is incredible – if you want to tackle hard and interesting problems at scale, and create an impact within an entrepreneurial environment, join us!

Your Key Responsibilities
Use data to inform and influence the direction of the product team roadmaps inform business decisions
Partner with product teams to define goals and identify key metrics for existing features and new releases
Build automated dashboards and reports to drive awareness and understanding of key metrics and experiment results
What To Bring
Bachelor’s degree in Computer Science, Engineering or related field, or equivalent training or work experience
A proven track record of using data to impact key business or product decisions
The ability to clearly and effectively communicate the results of complex analyses
Minimum of 4 years experience writing production datasets in SQL/Hive OR building internal/production data tools for ETL, experimentation, or exploration in a scripting language (Python, PHP, Ruby, etc.)
A solid grasp of common statistical applications and methods

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