Principal Specialist Data Scientist at Vodacom

We’re at our best when we lead and over the past 20 years, as the Company that pioneered mobile in South Africa, Vodacom has achieved a remarkable list of firsts. We’re immensely proud to be a leader in our field and are 100% committed to continue trailblazing.
We employ individuals who are as passionate about customers as we are. We are truly Customer Obsessed which means that we are passionate about exceeding customer expectations; work relentlessly to really understand the customer; look at decisions through the customers eyes and take personal accountability for the customer experience.

Your Responsibilities Will Include

• Works in partnership with Technology and local BI and analytics teams to agree on pragmatic means of data provision to support use cases
• Contributes to the development of self and others across the global analytics community, ensuring Advanced Analytics is always evolving and at the cutting edge
• Professional and/or academic experience in Big Data analytics & deployment of models and algorithms to solve real- world problems (with deep statistical 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)

The Ideal Candidate For This Role Will Have

• Bachelors or Masters Degree in quantitative fields like Mathematics, Statistics, Economics, Computer Science Engineering, Artificial Intelligence, Social Sciences, Data Journalism, or related fields
• A minimum of 5 to 8 years’ experience in the following:
• 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