An Evergreen Requisition is an advertisement for positions that Safaricom PLC hires for throughout the year. It is a way for Safaricom to build a database of qualified, interested individuals for a particular job function so that when there is a need to fill that type of role, the hiring process will be faster. By applying to an Evergreen Requisition, you are expressing your interest for a particular job function within the Safaricom family.
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The Data scientist will lead the data science team to create value from Safaricom’s vast amount and variety of data using advance analytical and statistical methods and models to answer complex business questions. This will serve to aid in decision making, unlock new revenue opportunities and areas to create efficiency through deep insights. The role requires deployment of Artificial Intelligence driven by Safaricom’s data to create Machine learning models and solutions to deliver specific business relevant use cases. Safaricom is investing heavily in big data and this will be a truly exciting role in view of the organizations unique data set and position in this region.
Responsibilities
Data mining using state-of-the-art methods
Selecting features, building and optimizing classifiers using machine learning techniques
Processing, cleansing, and verifying the integrity of data used for analysis
Collaborate with business units and engineering teams to understand and prioritize company needs and devise possible solutions based on business use cases
Create various machine learning-based tools or processes within the company, such as recommendation engines or automated lead scoring systems to drive revenue or create cost efficiencies
Create visualizations using state of the art visualization tools
Lead and manage data science team
Qualifications
BSC. or MS. in Computer Science, Statistics, Mathematics or equivalent practical experience
2 – 10 years data science working experience and with a leadership role.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests
Experience with common data science toolkits, such as R, Weka, NumPy, MatLab
Experience with data visualization tools, such as D3.js, GGplot
Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
Good applied statistics skills, such as distributions, statistical testing, regression
Good scripting and programming skills
Good understanding of big data technologies like Hadoop
Strong communications and interpersonal skills and quick grasps to understand business problems
