Data Analyst (HR)
Data Analyst - HR
Vodafone is a rapidly advancing company, pushing the boundaries of what and how a Telecommunications company in the UK operates and delivers for its customers. As part of this effort, HR are in the middle of a data revolution and are growing their People Analytics Function to drive the HR agenda and help Vodafone become a fully data-driven company.
Is this role for me?
We are looking for a Data Enthusiast with an insane passion for applying their programming and analytical skills to solve business problems and drive business outcomes.
They will be part of our growing people analytics team at Vodafone UK: our mission is to understand the link between business KPIs and our people metrics and help transform HR into a data-driven organisation that breathes and thinks data.
What will I be doing?
This is a very exciting role that sits between business and analytics, data science and strategy, with a great growing potential and that will give you the opportunity to have a direct and recognisable impact on Vodafone’s business performance and strategy.
In your new role you will:
• Develop innovative data-driven automated processes to support HR simplification process
• Dive deep into our people and business data to conduct advanced analytics, extract insights, and use data visualisation and storytelling to engage business audiences in a compelling way
• Work on the end-to-end integration of internal and external data sources and ensure the right quality checks are in place at the various stages of the acquisition process
• Interact with a large number of both technical and non-technical teams from across the company
Who are we looking for?
• Degree educated, preferably in a quantitative fields (including, but not limited to, Computer Science, Mathematics, Statistics, Economics, Social Sciences)
• Experience in data manipulation e.g. SQL, unstructured data tools a plus
• Experience in a programming language e.g. Python, Java, C++
• Some experience of statistical modelling/machine learning techniques (e.g. k-means segmentation, regression, time series analysis) desirable
If all of above sounds good to you - apply now!
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