Senior Executive-Data Science and Advanced Analytics Specialist

About VOIS

About the role

What you will do

• Develop and deploy descriptive, inferential, predictive, and prescriptive analytical solutions.
• Translate business challenges into clear analytical requirements, deliverables, processes, and expected outcomes.
• Use existing data models and analyses to support business outcomes.
• Develop predictive models with measurable business impact.
• Improve delivery through automation, standardisation, and reuse or redesign of existing solutions.
• Analyse structured and unstructured datasets containing tens of millions of records.
• Apply machine learning, deep learning, clustering, segmentation, classification, forecasting, and regression techniques.
• Visualise results and present actionable findings to business stakeholders.
• Create reusable analytical products with documentation and relevant training.

Who you are

• Have at least two years of practical experience in data science and analytics.
• Have hands-on Python experience, including at least six months on live projects.
• Understand machine learning, analytical, and statistical techniques.
• Have completed at least three modelling projects across different business areas, including predictive modelling with measurable commercial impact.
• Can manipulate and analyse very large structured and unstructured datasets.
• Can communicate complex analytical concepts clearly and present findings effectively.
• Bring a flexible, practical, and collaborative problem-solving approach.
• Have a relevant graduate qualification and a sound academic record.

Additional skills

• Experience with R, SAS, Google Cloud Platform, Amazon Web Services, Hadoop, Hive, or Pig is beneficial.
• Previous telecommunications experience is advantageous.

What you will gain

• Exposure to varied business challenges, large-scale datasets, analytical use cases, reusable products, cloud platforms, and big data technologies.
• Opportunities to develop predictive and prescriptive modelling, analytical storytelling, automation, and standardisation skills.