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We are currently in search of people with in-depth knowledge of mathematical and statistical modeling to take part in the group developing our automatic data analysis toolkit that is deployed both internally in the Ericsson RAN labs and in customers’ networks. Network Analysis is, to a large extent, currently a human activity, but our mission is to automate this work by preparing information and finding patterns, anomalies, and insights with data analysis techniques. Your objective will be to develop statistical and machine learning models based on customer network data in a big data platform.

The position includes the following activities and responsibilities:

• Perform time series and count regression analyses on network data

• Develop robust anomaly detection models by merging several different data types from customer networks

• Use feature engineering too extract the best features for a problem and apply suitable regularization techniques for robust analysis

• Use machine learning methods to produce insights from network performance and configuration data

• Create new statistical models to correlate data from several different sources

• Create quality software in R, Python, Java, Scala, or Matlab to access, process and analyze data

• Breaking down business problems into statistical and machine learning problem formulations for actionable insights

• Designing statistical experiments to evaluate and validate deployed statistical approaches

Job Summary:

We are currently in search of people with in-depth knowledge of mathematical and statistical modeling to take part in the group developing our automatic data analysis toolkit that is deployed both internally in the Ericsson RAN labs and in customers’ networks. Network Analysis is, to a large extent, currently a human activity, but our mission is to automate this work by preparing information and finding patterns, anomalies, and insights with data analysis techniques. Your objective will be to develop statistical and machine learning models based on customer network data in a big data platform.

The position includes the following activities and responsibilities:

• Perform time series and count regression analyses on network data

• Develop robust anomaly detection models by merging several different data types from customer networks

• Use feature engineering too extract the best features for a problem and apply suitable regularization techniques for robust analysis

• Use machine learning methods to produce insights from network performance and configuration data

• Create new statistical models to correlate data from several different sources

• Create quality software in R, Python, Java, Scala, or Matlab to access, process and analyze data

• Breaking down business problems into statistical and machine learning problem formulations for actionable insights

• Designing statistical experiments to evaluate and validate deployed statistical approaches

Qualifications

• M.Sc., Ph.D. or equivalent competence in Statistics or machine learning?

Requested competence:

• Excellent competence in mathematics and statistics.

• Competence in machine learning techniques and algorithms

• Knowledge about big data platforms such as Hadoop, Spark, Kafka, Storm or Flink.

• Competence in R, Python, Matlab, Java or Scala

Why is Ericsson a great place to work?

Ericsson is the driving force behind the Networked Society where every person and every industry is empowered to reach their full potential. Mobility, broadband and the cloud are transforming the world, enabling industries and society to provide better services, capture new opportunities, improve businesses, increase efficiency, and create new user experiences.

Our services, software and infrastructure support every major telecom operator in the world. The transformation that this brings allows people, business and society to fulfill their potential and build a more sustainable future.

Detta är en jobbannons med titeln "Statistical modelling and machine learning" hos företaget Ericsson AB och publicerades på webbjobb.io den 8 september 2017 klockan 00:00. Jobbannonsen kommer från en extern källa.

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