Senior Data Scientist
Ericsson is world’s leading provider of communications technology and services. Our offerings include services, consulting, software and infrastructure within Information and Communications Technology.
Using innovation to empower people, business and society, Ericsson is working towards the Networked Society: a world connected in real time that will open up opportunities to create freedom, transform society and drive solutions to some of our planet’s greatest challenges.
We are truly a global company, operating across borders in over 180 countries, offering a diverse, performance-driven culture and an innovative and engaging environment. As an Ericsson employee, you will have freedom to think big and the support to turn ideas into achievements. Continuous learning and growth opportunities allow you to acquire the knowledge and skills necessary to progress and reach your career goals. We invite you to join our team.
Ericsson is now looking for Senior Data Scientists to significantly expand its global team for AI acceleration in Plano, TX.
Do you have in depth understanding of Machine Learning and AI technologies?
Do you want to join Ericsson’s global team of Data Scientists pushing the technology frontiers to automate, simplify and add new value through data?
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.
- B.Tech/MS in Computer Science, Engineering, Data Science, Operations Research, Business analytics, related fields
- 8 to 10 years experience of academic, research and real world Data Science training and solutioning
- 3 to 5 years of practical development of machine learning and artificial intelligence models and algorithms
- 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.
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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