We are looking for a talented Data Scientist to join an ever-growing ambitious team of Data Scientists in Ericsson! This position will join local and global fellow scientists working on a variety of data science projects linked to Ericsson’s products and services at our Plano HQ.
Responsibilities & Tasks
• Conduct product development studies based on Machine Learning/AI techniques targeting implementation into mobile telecom networks and network management products such as self-healing, self-maintenance, and self-optimization
• Perform telecom network investigations with domain experts to understand system behavior and network performance. Based on network data analysis, identify performance improvement areas and develop ML-driven actions for implementing them
• Evolve methods to analyze network performance and system behavior using all available data sources
• Understand, adapt and apply machine learning and AI techniques in the telecom network context for product monitoring, product troubleshooting and product implementation purposes. Develop new techniques if required
• M.Sc. or equivalent working experience in data science
• Excellent understanding of applied mathematics and statistics
• 7 to 10 years of documented experience in machine learning, deep learning, data mining and big data modeling, especially in time series analysis, classification, regression, clustering and recommender systems
• Familiar with Big Data management techniques (e.g. Hadoop ecosystem, SPARK, Flink)
• Excellent scripting and programming skills (e.g. R, Python, Java, Scala, bash shell)
• Experienced user of business intelligence and exploration tools (e.g. Tableau, SAS Analytics, Power BI or similar)
• Expert level in SQL
• Understanding of mobile network technologies in general and 4G(LTE) in particular is a plus
• Experience from Product Development and System management is a plus
• Experience from working in Lean and Agile environments is a plus
DISCLAIMER: The above statements are intended to describe the general nature and level of work being performed by employees assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of employees assigned to this position. Therefore employees assigned may be required to perform additional job tasks required by the manager.
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