Job Description
DESCRIPTION
We are pleased to announce the following vacancy Lead Data Scientist within Big Data and Business Analytics department in Finance Division. In keeping with our current business needs, we are looking for a person who meets the criteria indicated below.
Brief Posting Description
Reporting to the Head of Big Data and Analytics, the position holder will create value from Safaricom’s vast amount and variety of data using advance analytical and statistical methods and models to answer complex business questions to aid decision making, unlock new revenue opportunities and areas to create efficiency. 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.
Job Responsibilities
• Co-creating ML products that provides actionable insights to Safaricom
• Development of ML models and recommendation systems with large varied datasets for various business units on the Big Data Platform, working with the community of data colleagues across technology, data and business
• Drive revenue impact and cost-efficiencies using Big Data
• 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/ Tribes and data engineering/ML Ops teams to understand and prioritize company needs and devise possible solutions based on business use cases
• Development of prototype code in PySpark for automated training & scoring of the ML models
• Create visualizations to track ML model performance using state of the art visualization tools (e.g. Qlik)
• Use data visualization to engage audience in a compelling way, demystifying ML through effective storytelling
• Lead and manage data science team
• Contributing towards Revenue, Customer Experience and Cost Efficiency metrics using Big Data
QUALIFICATIONS
Job Requirements
• BSC or MS in computer science, Statistics, Mathematics or equivalent practical experience
• 1 – 2 years experience in any cloud platform and ML lifecycle (e.g. AWS. GCP)
• 5 – 8 years data science working experience and with a leadership role.
• Experience in machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, gradient boosting, factor analysis, time-series forecasting)
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab
• Experience in major ML libraries (e.g. H2O, Scikit-learn, PyTorch)
• Experience with data visualization tools, such as D3.js, GGplot
• Experience with Data Manipulation (Unstructured data tools and platform – NoSQL, Hadoop, Spark and structured data tools (e.g. SQL)
• Good applied statistics skills, such as distributions, statistical testing, regression
• Good scripting and programming skills (e.g. proficiency in Python)
• Good understanding of big data technologies like Hadoop
• Experience in digital assets (i.e. social listening, social network analysis)
• Strong communications and interpersonal skills and quick grasps to understand business problems proven ability to self-start and effectively manage multiple assignments.
• The ability to work under pressure and be resilient and tenacious to get results
Note to Applicants
As part of the interview process, external candidates should prepare the following documentation which will be required as soft copies at a later stage based on your performance in the interviews/assessments.
a) An updated CV with contacts of three referees, 2 who must be professional and must have supervised you at some point, the other referee can be a colleague in the same professional field.
b) Kenyan Certificate of Good Conduct (Less than 1 year old) or a receipt of the same from the CID pending release of the hardcopy document.
c) Clearance certificate from a reputable Credit Reference Bureau (CRB).
d) University Diploma/Degree Certificate/ Letter of completion from university in case you have not received your diploma/degree certificate.
e) National ID/Passport.