Specialist Data Scientist

Would you like to be part of our new adventure? Vodafone Group launched its new technological HUB in 2021, an international center of excellence dedicated to research and development of technical solutions, such as Secure Networks, 5G and 6G development, Open RAN, IoT, MPN & MEC and UCC for Vodafone Business, platforms and enterprise solutions.
This vacancy is part of VOIS Spain, legal entity part of Vodafone Group.
Come and join us to create the future together!

We are looking for a Data Scientist to join our Vodafone Business Data & Artificial Intelligence team, to work alongside 20+ experienced, dynamic, and passionate data scientists focused on both internal and external data monetization projects. Some of our exciting projects include data engineering massive volumes of real-time, location-based data and then applying statistical analysis, making predictions on time series data, and running simulation scenarios to make recommendations, utilizing unsupervised learning to detect anomalies, developing data visualizations and dashboards for different business areas, deploying supervised learning models in production on public cloud architectures to optimize marketing campaigns, etc. If these projects spark your interest, you love technology and its applications, and you are an effective team player with excellent communication skills...we are looking forward to meeting you!

For the role of Sara Scientist we are looking for candidates with a broad range of skills. The responsibilities include:

Data Science: Descriptive and predictive analytics: selection, definition, and execution of adequate algorithms, models, tests, visualizations, etc.
Technology: Selection, definition, and execution of adequate programming frameworks, file formats, data storage solutions, automatic data flows, etc.
Architecture: Define and/or follow best practices for Big Data & Analytics & AI use cases using on-premises solutions as well as public cloud services.
Management: Report to project managers, clients, external and/or internal teams. Estimate resources and timelines for different tasks during the project life cycle.
Innovation: Awareness of and continuous training in state-of-the-art techniques, models, frameworks, and tech approaches to be applied to DS & AI activities.

What you bring:

Degree in Computer Science, Engineering, Mathematics, or related field, required
2 years of professional experience in Data Science related positions, required
English proficiency, required
Master’s in Data Science, AI, Data Engineering, or any data-related field, desired
PhD and/or research experience, desired

Required Technical skills:

Experience with handling code repositories using Git.
Expertise in at least one Cloud environment (preference on GCP, AWS) on data related services

Nice to have:

Proficiency in Python: experience handling and contributing to complex Python projects (multi-module projects, Object Oriented Programming projects – inheritance and classes, inter-dependencies between projects), building quality and production-ready code in a complex project using an IDE.
Proficiency in Spark: understands the concept of Spark DAG, master node, executor nodes, experience on debugging a Spark execution using the Spark UIs (e.g. debugging a memory error), knows how to appropriately size up and set up a Spark cluster (either in Dataproc - GCP, or in EMR - AWS), and to choose th manipulation and Machine Learning (e.g., pandas, scikit-learn), with special emphasis in distributed computing frameworks (e.g., PySpark).
Apply appropriate ML and AI models to problems, evaluating the outcomes to maximize business impact with critical thinking.
A strong understanding of probability theory, statistical inference, hypothesis testing, and experimental design is required for decision making with data.
Data visualization, bringing data-driven solutions and business context together.
Knowledge of designing and building APIs with best practices.
Deploying and supporting Machine Learning models in live cloud environments: ML Engineering and MLOps in AWS/GCP/Azure.
Applying Data Engineering best practices for designing, building, and maintaining data pipelines and ETL processes (e.g., Apache Airflow).

Please, apply with an English version of your CV.

Why Vodafone?
At Vodafone, we are dedicated to fostering a diverse and inclusive work environment. We take pride in our commitment to providing equal opportunities to individuals of all backgrounds and abilities. We firmly believe that diversity includes a spectrum of experiences, and we welcome and support individuals with functional diversity.

Our mission is to create an accessible workplace where all team members can thrive, regardless of their unique abilities or challenges. We are committed to making reasonable accommodations to ensure that everyone can fully participate and excel in our organization. We value the unique perspectives and talents that individuals with functional diversity bring to our team and consider them an integral part of our success and innovation.
We recognize and celebrate the importance of diversity and inclusivity in our workplace so that we are as diverse as the customers and communities we serve. 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.
Worried that you don’t meet all the desired criteria exactly? At Vodafone we are passionate about Inclusion for All and creating a workplace where everyone can thrive, whatever their personal or professional background. So, if you’re excited about this role but your experience doesn’t align exactly with every part of the job advert, we encourage you to apply as you may be just the right candidate for this role or another role, and our recruitment team can help see how your skills fit in.

Benefits: