We are now looking for a Data Scientist / Data Engineer Intern for ML/AI to develop and maintain components that deliver Telecom Insights on top of Ericsson Expert Analytics (EEA) portfolio!

EEA is a powerful tool offered to telecom operators producing customer insights in real time. Backed by specialized metrics for predicting customer happiness, EEA provides the kind of deep understanding of customer behavior that allows service providers to proactively improve experience, satisfaction.
Link: https://www.ericsson.com/en/network-automation/telecom-analytics

We are expanding our Budapest EEA development and support organization. We work in small teams that use Agile methodology to keep up in a fast-paced business environment, we closely cooperate with Ericsson Research, customer units and service delivery organization. Our product platform combines cloud based solutions with Big Data methodologies with our outstanding complex event processing to build a state-of-the-art analytics and decision management system.

You will

• Work with / as a Data Scientists on diverse use cases
• Automate and scale model training, inference and evaluation
• Integrate ML pipelines and configure them on Kubernetes
• Become familiar with Kubernetes and Docker containers
• Collaborate with various teams, such as Data Scientist team, DevOps teams, BI team and business stakeholders
• Get familiar with the data structure – this requires continuous knowledge transfer from our telecommunications experts, so you’ll get familiar with the telco domain as well
• Help work with real big data processing pipelines, prepare data for predictive and prescriptive modeling
• Help us conducting different analytical tasks to better understand the fundamental relationships behind our datasets, improving the quality of our modeling activity
• Help us finding approaches that are capable of handling large volumes of data (terabytes)
• Work hand-in-hand with telco experts to come up with machine learning and statistical models to solve network monitoring/optimization and marketing related tasks
• Learn working with parallel algorithms
• Take part in brainstorming sessions where the aim is to find use-cases that are both valuable to customers and feasible as well
• Learn how to create proof-of-concept models and how to develop and integrate them into production level codebases
• And most importantly: you will have to read and learn a lot, both from our data scientists and from books/articles/blog posts
• Work on own patents and inventions

To be successful in the role you have experience or strong willingness to learn in the following areas

• A degree in Computer Science, Information Technology, or a related field is a great foundation.
• A background or interest in data engineering or machine learning is valuable.
• Hands-on experience with Python and SQL
• Familiarity with database and storage technologies such as Vertica, S3 MinIO, and PostgreSQL is beneficial
• Understanding of methodologies like continuous integration and continuous delivery
• Understanding of containerization technologies like Docker and Kubernetes
• Previous experience with data in manufacturing/operations environment would be a plus
• Experience with Code and Data versioning: we use Gerrit and DVC
• Enthusiasm for MLOps and the ML project lifecycle (Data Preparation, Modeling, Deployment, and Monitoring) is encouraged
• Interest in designing, implementing, and maintaining data pipelines in event-driven, microservices-based distributed systems is a plus.
• Interest in best practices like code refactoring, design patterns, design-driven development, continuous deployment, building scalable applications, and application security is welcome.

It's a huge plus if you have

• Experience in Kubernetes operations and maintenance
• Industry experience in building and productizing end-to-end analytics system of Machine Learning and Data Scientist projects
• Good knowledge of any distributed computing tools such as PySpark, Dask, Ray
• Experience in working with AWS, Azure or GCP cloud provider (certifications are a huge plus)
• MLOps experience in terms of model monitoring, data drift detection, re-training implementation, model roll-back, for machine learning solutions
• Experience with Big Data technologies, stream processing (e.g.: Hadoop, Kafka)
• Experience with reporting BI tools (e.g. Spotfire, Tableau)
• Ability and willingness to quickly adopt new technologies and/or business domains
• Experience in Telecommunication Industry

We offer you

• A supportive multinational environment, where we believe in teamwork
• Great challenges that will give you the opportunity for continuous learning and advancement in your technical career
• To work with a talented group of Data Scientists, DevOps teams and BI developers, who will help to develop new ideas and solve complex problems of the network
• To work on big projects that will go into production, so you will not work for your desk drawer
• In our view for the continued sharpness of mind, regular brain exercise is required. To ensure this opportunity is provided across the board, trainings and conferences are encouraged and supported

What happens once you apply?

Click here to find all you need to know about what our typical hiring process looks like. This may vary depending on the location and role.
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Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we nurture it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team.
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Primary country and city: Hungary (HU) || Budapest

Req ID: 762975