Vodafone

Data Scientist

Italy
TensorFlow Microservices Hadoop Kubernetes SQL Pandas Machine Learning Python AWS GCP
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Description

Role purpose:


The role will be part of the VNO Digital function.

The team has as main objective to automate Network Operations processes, in particular:
- Interact with Network operations teams to identify, develop and industrialize data science and analytics use cases, suited to the needs of Italian market
- Evaluate ZTO vendor solutions and coordinate their integration with our platforms
- Automate Field management processes 

In the described scope, the successful candidate will be responsible of identifying most profitable data science/big data business cases, implement machine learning python prototypes and deploy industrialized code on available platforms (Cloudera Hadoop, cloud AWS/GCP or Kubernetes based platforms), with the help of data engineering team.
She/He will be also able to perform and provide technical leadership for data analysis and support on data-driven business decisions. She/He will be leading data management choices and architectural solutions. 
 

Key accountabilities and decision ownership:


• 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/K8 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 

Core competencies, knowledge, and experience:

• 2+ years 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)

Must have technical / professional qualifications:


• Degree in Computer Science, Maths, Engineering or equivalent
• 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 over time series, Gradient Boost and all other main ML models both supervised and unsupervised)
• Excellent analytics and mathematics skills

Nice to Have:


• Experience in the usage of BI reporting tools (Qlik / power BI / Tableau)
• Experience in coding in microservices, within Docker-based architectures, in Cloud or On-prem platforms
• Knowledge of DevOps pipeline and main tools for code versioning, automatic testing and continuous integration in both On-prem and Cloud environments   
• Data Architect or Cloud Certifications
 

Who we are

You may have already heard of Vodafone - We're a leading Telecommunications company in Europe and Africa. But what you might not know is that we are continuously investing in new technologies to improve the lives of millions of customers, businesses and people around the world, creating a better future for everyone.

As part of our global family, whether that's Vodafone, Vodacom or _VOIS, you'll feel a sense of pride and purpose as you contribute to our culture of innovation. We pursue equality of opportunity and inclusion for all candidates through our employment policies and practices. We recognise and celebrate the importance of diversity and inclusivity in our workspace and we do not tolerate any form of discrimination especially related to but not limited to race, colour, age, veteran status, gender identification, sexual orientation, pregnancy, ethnicity, disability, religion, political affiliation, trade union membership, nationality, indigenous status, medical condition, HIV status, social origin, cultural background, social, or marital status.

Together we can.

Vodafone
Vodafone
E-Commerce Industrial Manufacturing Plastics and Rubber Manufacturing Retail Information Technology Messaging Mobile Apps Mobile Devices Network Security Telecommunications

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