Principal Data Scientist

Responsibilities

• Create Machine Learning and AI products that provide actionable business insight and drive personalisation for M-Pesa users.
• Developing predictive models with large and varied datasets, working with a community of colleagues across Advanced Analytics, technology, and data and customer functions.
• Development of machine learning models 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.
• Uses data visualisation to engage audience in a compelling way, enabling effective storytelling.
• Work with lead data scientist to deliver key packages of work 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 product ionising.
• Contributing to the wider community to enable Machine Learning and AI capability across Vodafone globally.
• Manages and takes ownership of a portfolio of work from model development to stakeholder engagement.

• Bachelor’s or Master’s Degree in quantitative fields like Mathematics, Statistics, Economics, Computer Science Engineering, Artificial Intelligence or related fields (essential).
• 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).
• Familiarity with visualisation tools (e.g. Tableau, Qlik, D3).
• Experience working with large datasets (e.g. SQL, Hadoop, Spark, No
  
  SQL).
• Proficiency in at least one relevant programming language:
  Python, R.
• Experience 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).