Work at Naspers
Naspers Classifieds is currently present in 40+ countries and boasts over 200 million active monthly users worldwide, generating more than 11 billion monthly page views. These accumulate to petabytes of invaluable data. Naspers therefore acknowledges the dominant roles of modern technology, big data and product innovation in the online industry in general and at Naspers in particular. Therefore, great effort and attention are put into hiring the best people available from the world over for the Customer Lifecycle Management (CLM) team. The team will consist of tech-savvy professionals with complimentary and synergizing skills in data science, data engineering, customer experience, personalization and product management. Two job descriptions are listed below, but candidates with skills overlapping both are very welcome in this team and will find their responsibilities adjusted accordingly.
The Data Scientist/Engineer will upgrade innovation to disruptive levels. How? By analyzing the vast amounts of data on customer behavior on the different platforms, identifying value pockets and communicating actionable insights to the Product, Marketing and Customer Care teams.
The CLM team is very agile, so roles are subject to constant change. A Data Scientist / Engineer starting today would work on:
- Mining the database of raw customer behavior data (> 1 petabyte, billions of rows and > 100 million customers) to generate best-in-class insights)
- Setting up and maintaining analytical (big) data environments including distributed data structures
- Using machine-learning algorithms to discover and identify actionable patterns in data
- Developing and building customer-centric predictive models for customer lifetime value and churn
- Developing and maintaining actionable customer segmentation
- Translating business problems into analytical methodology
- Promoting data-science across Naspers as a thought leader and guiding stakeholders in unlocking the value in their data
- Communicating complex analysis in a clear, understandable way to non-expert global and local teams
Candidates are selected on their high ambitions and winner’s attitude as much as their skills and experience. Relevant experience and skills include:
- Broad experience conducting customer analytics on large data sets
- PhD or Masters in a quantitative discipline
- Stellar SQL skills across a variety of relational data warehousing technologies
- Experience with NoSQL databases
- Skilled with setting up and managing distributed Hadoop clusters and developing MapReduce algorithms using a variety of technologies
- Advanced skills in building models and experience with statistical analysis, machine learning and data mining
- Experience working with Amazon Redshift is a plus.