At Ericsson, you can be a game changer! Because working here isn’t just a deal. It’s a big deal. This means that you get to leverage our 140+ years of experience and the expertise of more than 95,000 diverse colleagues worldwide. As part of our team, you will help solve some of society´s most complicated challenges, enabling you to be ‘the person that did that.’ We’ve never had a greater opportunity to drive change; setting the bar for technology to be inclusive and accessible; empowering an intelligent, sustainable, and connected world.

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Data Scientist

Job Description

Date: Nov 6, 2019

Data Scientist


Education: B.Tech/MS  in Computer Science, Engineering, Data Science, Operations Research, Business analytics, related fields


Qualifications for Data Scientist

  • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
  • Knowledge of deploying applications using docker and kubernetes.
  • Experience working with and creating data architectures.
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Experience manipulating data sets and building statistical models
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
  • Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
  • Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
  • Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.



Responsibilities for Data Scientist

  • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
  • Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Develop custom data models and algorithms to apply to data sets.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
  • Develop company A/B testing framework and test model quality.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor and analyze model performance and data accuracy.