Data Scientist at Vodacom

Job description

Ideal Candidate should be a;

• Data Scientist with Co-creating Advanced Analytics products experience. Must be able to 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.
• Must Contribute to the wider community to enable an Advanced analytics capability across Vodafone globally.Expert in machine learning, artificial intelligence, cognitive computing.
• Expert in machine learning, artificial intelligence, cognitive computing.
• Hands-on experience with Big Data technology, including Hadoop and related tool set (Spark, Scala, Sqoop, Mahout); both SQL and NoSQL database structures.
• In-depth knowledge of advanced statistical techniques, e.g., random forest, Hidden Markov Models, multidimensional scaling, bootstrapping, matrix algebra, graph theory.
• Programming ability in at least two languages, Python and C++ preferred; web development experience preferred.
• Experience implementing complex models and algorithms in digital settings, e.g., apps, chatbots
• Working knowledge of webscraping and open APIs, social media data.
• Commercial focus, with proven demonstration of value from analytical models

Advanced degree required in computer science, statistics, or a related field.

• Bachelor’s or Master’s Degree in quantitative fields like Mathematics, Statistics, Economics, Computer Science Engineering, Artificial Intelligence, Social Sciences, Data Journalism, 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 at least one relevant programming language: Python, Scala, MapReduce, Mahout, Java, C++
• Expertise in major statistical modelling software packages (e.g., R, SAS) and multivariate techniques (e.g. 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