Ericsson Hiring Data Scientist

Location: Chennai
Experience: 2 – 4 years
Role: Data Scientist

Job Summary

As a Data Scientist, you will need to have strong programming skills and deep understanding of data science and Machine Learning tools. Have proven experience in Data Science methodologies and how to apply them to solve challenging real-world problems as part of a highly dynamic and global team. You have strong communication, collaboration and planning skills. You will be working on high impact initiatives with other specialists in Machine Intelligence to drive growth and economic profitability for Ericsson and its customers by accelerating current Ericsson offerings as well create new offerings in the areas of MI driven 4G and 5G network, distributed cloud, IoT and other emerging businesses.

Key Qualifiications

  • Education: Bachelor in Engineering (B.E/ B.Tech in IT, Telecom)
  • Minimum years of exp-12+years
  • Proven skills and track record (Github, open source etc.) in the use of current state of the art machine learning frameworks such as Keras, TensorFlow, Scikit-Learn, H2o, Spark etc. in developing ML/AI applications
  • Experience of data wrangling and data munging, using Big Data technologies
  • Strong analytical skills and ability to acquire new knowledge and apply it in the job
  • Programming skills in various languages (C++, Scala, Java, R) with proficiency in Python and/or C++
  • Good communication skills in written and spoken English
  • Creativity and ability to formulate problems and solve them independently
  • Ability to develop and drive new ways of working, to produce deliverables in a more efficient way

Key Responsibilities

  • Experience with data visualization and dashboard creation
  • Certifying MI MOOCS, a plus
  • Applications/Domain-knowledge in Telecommunication and/or IoT, a plus.
  • Ability to build and nurture internal and external communities
  • Experience in writing and presenting white papers, journal articles and technical blogs on the results
  • Ability to work in a collaborative environment, i.e., working with complex multiple stakeholder business units, global customers, technology and other ecosystem partners in a multi-culture, global matrix organization with sensitivity and persistence