What you’ll do
As a data scientist, you will drive real-world impact by applying innovative data-driven technology to our ever-growing dataset. You will be responsible for the end-to-end data science project lifecycle, starting from problem scoping to machine learning systems deployment and maintenance. The ideal candidate possesses a strong analytical ability to solve complex problems with data
Key Accountabilities
Create Machine Learning and AI products that provide actionable business insight to Vodafone and its stakeholders.
Developing predictive models 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 Machine Learning and AI capability across Vodafone globally.
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
Work with Vodacom Group lead data scientists to deliver key packages of work to meet the needs of business customers
Works in partnership with Group Big Data Engineering for data ingestion to support use cases
Competencies
Experience in major machine learning modelling libraries (e.g., H2O, scikit-learn, PyTorch, Tensorflow) and techniques (e.g. random forest, gradient boosting, k-means segmentation, multiple regression, factor analysis, time-series forecasting)
Exposure to cloud native deployment of models and working with Containerised technologies such as Docker and Kurbernetees.
Knowledge of MLOPS concepts and deployment of models through batch and real-time architectures. Use of Technology such as (MLFLOW and Apache Airflow)
Familiarity with visualisation tools (e.g. Tableau, Qlik, D3, Apache Superset, Plotly)
Exposure/interest in machine learning
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)
Qualifications and Experience
Bachelor’s degree in quantitative fields like Mathematics, Statistics, Computer Science Engineering, Artificial Intelligence or related fields (essential)
A minimum of 3 years relevant experience in Data Science.
Experience in data manipulation: use of structured data tools (e.g., SQL), and unstructured data platforms (e.g., Hadoop, Spark, NoSQL)
Proficiency in at least one relevant programming language: Python, R
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