This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
At Vodafone, we’re not just shaping the future of connectivity for our customers – we’re shaping the future for everyone who joins our team. When you work with us, you’re part of a global mission to connect people, solve complex challenges, and create a sustainable and more inclusive world. If you want to grow your career whilst finding the perfect balance between work and life, Vodafone offers the opportunities to help you belong and make a real impact.
Job Responsibility:
Identification of data science / big data / analytics use cases for Network Operations and architectural High Level Design
Choice and implementation of the best machine learning algorithm suited to the use case
Industrialization of the use cases on Cloudera, Openshift/Kubernetes or on AWS/Google cloud environments, with the support of data engineers
Technical leadership in analysis and data management domains
Data-driven evaluation of vendor product adoption
Requirements:
Degree in Computer Science, Maths, Engineering or equivalent
Junior Profile with Experience in similar position (Max 2 years)
SQL, Python (Pandas, Tensorflow, Scikit-learn, and main other ML libs), Pyspark and SW development capabilities
Machine learning algorithms knowledge (NLP, Neural Networks., Random Forest, SVM, Anomaly Detection especially on time series, Gradient Boost and all other main ML models both supervised and unsupervised)
Knowledge of deployment best practices and DevOps pipeline
Excellent analytics and mathematics skills
Professional English (spoken and written)
Experience in Machine Learning SW development and data analysis
Experience in designing and implementing use cases over big data architectures involving massive data volume, also under real-time constraints
Knowledge of pros and cons of existing data storage technologies (relational DB, Big Data Frameworks, no-SQL DB on cloud and on prem)