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Data Scientist

Responsibilities:
* Major contributor of continuous improvements in the quality of data analysis and modeling in Hotstar
* Keep track of both industry and academic research trends in related areas including but not limited to machine learning, data science and distributed computation
* Participate in data science projects planning with product managers and the team based on data-driven investigation methods and industry trends. 
* Propose, implement, test and verify analytic and algorithmic solutions for upcoming data science product features.
* Implement systems that combine data science and product design to continuously improve over time.
* Develop prototype, proof of concept, and demo systems to improve performance for current algorithms and architectures.
* Implement the solutions involved in data science problems.
* Partner closely with other product teams across the organization to experiment with different algorithms and validate their effectiveness, while gaining knowledge of how DS works in all these products.

Qualifications

  • Experience: Master degree or above. 1+ year experience of practical algorithm design and implementation in data science related fields.
  • Has experience in backend development will be a plusKnowledge: Solid mathematics, computer science, data analysis and machine learning background.
  • Solid knowledge and hands-on experiences in big data processing and parallel computing frameworks such as Hadoop and Spark.
  • Problem Solving: Logical thinker with good problem solving and analytical ability to apply your mathematical, algorithmic and other expertise to solve real problems.
  • Learning Ability: Strong ability to master new technology in a short time and apply to solve practical problems.
  • Motivation: Passion for applied research and new technology, open to interdisciplinary work.
  • Collaboration: Participated in at least 1 team project and played an important role to push the projects forward with others.
  • Communication: Good communication skills; both verbal and written.