Specialist Data Science & Analytics

Role Purpose

• Identify opportunities to improve business outcomes using analytical techniques, working with Local Markets and Group to understand their requirements and find and/or develop appropriate analytical products.
• Build and deliver data science and GenAI models that drive value following best‑practices and standards (revenue upturn, cost decrease and/or customer & employee engagement improvements).
• Build and deliver automations which will help digital transformation of stakeholders.
• Partner with Product Manager & delivery teams within VOIS to deliver analytics solutions.
• Create, own and maintain reusable data science products and services that can be deployed across Vodafone.
• Drive innovation by employing new analytical techniques.

Key accountabilities and decision ownership

• Stakeholder management and engagement with new stakeholders from Group and OpCos to address their analytics needs and shape and define our Analytics Products/Projects Portfolio based on these requirements.
• Ensure best‑practices and standards for software development in Data Science are followed across the wider team.
• Own specification and delivery of analytical products and services.
• Manage analytics portfolio and products by continuous improvement of existing products and developing new products based on stakeholder needs.
• Develop new analytics solutions through descriptive, GenAI, predictive and/or prescriptive analytics techniques.
• Manage delivery through partner organisation in DAIS (Data & Analytics Integrated Services in Vodafone Shared Services).
• Maintain data sources and models up to date.
• Maintain up to date knowledge and emerging trends in analytics and challenge the status quo.

Key performance indicators

• Value created from delivery of analytics products and projects.
• Efficiency of delivery (return on investment) given by the standardization of the solutions delivered.
• Rate of innovations introduced to the company (focus areas of ML/GenAI/Automation).

Core competencies, knowledge and experience

• Experience in agile way of working.
• Strong communication skills with ability to influence senior stakeholders.
• Storytelling with data.

Must have technical / professional qualifications

• Hands‑on proficiency in Python for data analysis, automation, and AI/ML solution development, following software engineering best practices (version control, modular design, reusable components).
• Practical experience with any Cloud (GCP, Azure, AWS).
• Working knowledge of Machine Learning and GenAI solutions.
• Experience defining, building and supporting end‑to‑end analytics or AI products, from requirements gathering and design through to preproduction and production deployment.
• Proven experience collaborating across business, IT and delivery team.

Benefits

• Hybrid work model.
• Bonus on top of the gross salary.
• Flexible working hours from Monday to Thursday, and an intensive schedule on Fridays.
• Intensive Summer Schedule during July and August.
• Up to 20 days per year of 100% remote work from other locations.
• Private Health and Life Insurance for employees and family.
• 25 vacation days, plus December 24th and 31st off.
• Optional Pension Plan.
• Access to an online learning platform for continuous training.

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