Senior Data Scientist at Vodacom

• Co-creating Advanced Analytics products that provide actionable business insight to Vodafone and its stakeholders.
• Developing predictive models and recommendation systems with large and varied datasets, working with a community of colleagues across Advanced Analytics, technology, and data and customer functions
• Contributing to the wider community to enable an Advanced analytics capability across Vodafone globally.

Your Responsibilities Will Include

• Development of machine learning models and recommendation systems for various areas of the business on the Big Data Platform
• Development of prototype code in e.g. PySpark for automated training and scoring of the machine learning models
• Machine Learning Model performance tracking and reporting using e.g. Qlik
• Uses data visualisation to engage audience in a compelling way, enabling effective storytelling
• Delivers key packages of work, on time and in a collaborative manner to meet the needs of business customers
• Works in partnership with Big Data Engineering for data ingestion to support use cases
• Works in partnership with Big Data Production Data Engineering for model automation and productionising s
• Contributes to the development of self and others across the global analytics community, ensuring Advanced Analytics is always evolving and at the cutting edge

The Ideal Candidate For This Role Will Have

• Professional and/or academic experience in Big Data analytics & deployment of models and algorithms to solve real-world problems (with deep statistical and machine learning modelling expertise)
• Experience manipulating and analysing large and complex datasets
• Experience in visualisation, creating graphical static and interactive displays of data that clearly communicate insight (preferred)
• Good interpersonal communication and presentation skills
• Ability to work in a fast-paced environment across multinational functional teams
• Analytical and expansive thinking with a strong desire to deliver and develop

Must Have Technical / Professional Qualifications

• Bachelor’s or Master’s Degree in quantitative fields like Data Science Mathematics, Engineering, Statistics, Computer Science, Artificial Intelligence or related fields
• Expertise in data manipulation: use of structured data tools (e.g., SQL), & unstructured data tools and platforms (e.g., Hadoop, Spark, NoSQL)
• Proficiency in Python
• Expertise in major machine learning modelling libraries (e.g., H2O, scikit-learn, PyTorch) and techniques (e.g. random forest, gradient boosting, k-means segmentation, multiple regression, factor analysis, time-series forecasting)
• Experience in digital data sets, e.g., social listening, social network analysis)
• Familiarity with visualisation tools (e.g. Tableau, Qlik, D3)
• Exposure/interest in machine learning