Summary
Date Posted: Tuesday, February 18, 2020 , Base Salary: Not Disclosed

JOB DETAILS:
Kenya Commercial Bank Limited is registered as a non-operating holding company which started operations as a licensed banking institution with effect from January 1, 2016. The holding company oversees KCB Kenya - incorporated with effect from January 1, 2016 - and all KCB's regional units in Uganda, Tanzania, Rwanda, Burundi, Ethiopia and South Sudan. Fintech Department is responsible for driving the Bank's Digital Strategy; Product and Business development of digital capabilities with new technologies to increase functionality, usage and transactions for NPI. Also responsible for driving the Bank's products and transactional services via digital technologies for both individuals and businesses (SME & Corporate). The Data Analyst will be tasked with role of engineering terra-bytes of data into actionable insights and new products for our customers. .

Key Responsibilities:
• Transform large, complex datasets into pragmatic, actionable insights, leverage data to identify, quantify and influence tangible business gain by performing ad-hoc analysis and presenting results in reports, dashboards and charts.
• Provide test interfaces for users to test the reports and dashboards before being put on the production environment and carry out technical user training as required to enable users interpret BI solutions. Implement analytical model designs, perform any restructuring required, and review Dataset implementations performed by the Data engineer and BI developers.
• Selecting features, building and optimizing classifiers using Machine Learning techniques and data mining using Bank selected data mining tools. Enhance data collection procedures to include information that is relevant for building analytic systems, process, cleanse and verify the integrity of data used for advanced analysis by creating automated anomaly detection systems and constant tracking of its performance.
• Improve data foundational procedures, guidelines and standards and develop best practices for data management, maintenance, reporting and security.
• Implement statistical data quality procedures or test driven approach for quality assurance and conduct performance tuning to be able to optimize the application of statistical models and scripts
• Design, build, and maintain various parts of the data warehousing with respect to requirements gathering, data modeling, metric establishment, reporting production, and data visualization.
• Gather and process raw, unstructured data at scale into a form suitable for analysis then consolidate into the data warehouse in order to perform Business Intelligence and advanced analytics.

Job Skills: Not Specified

Qualifications;
• A Bachelor’s degree in Statistics, Data Sciences or related quantitative field. Masters is added advantage.
• A minimum 5 years proven performance in Data Science & Analytics.
• Experience with relational Databases such as Oracle, SQL queries, or OLAP cubes is preferred.
• Experience in development of Credit Score Cards will be an added advantage.
• Excellent understanding of Machine learning techniques and Algorithms, such as k-NN, Naive Bayes, SVM and Decision Forests.
• Experience with common Data Science toolkits, such as R, Python, Weka, NumPy, MatLab, etc.
• Excellence in at least R and/or Python is highly desirable.
• Proficiency in using query languages such as SQL, Hive, Pig and Experience with NoSQL databases, such as MongoDB, Cassandra, HBase.
• Good Applied Statistics skills such as Distributions, Statistical Testing, Regression Analysis with good Scripting and Programming skills.
• Knowledge of Agile Software Development process and performance metric tools.
• Experience extracting and cleaning text in different formats e.g. HTML, pdf files.

Job Education Requirements: Not Specified

Job Experience Requirements: Not Specified

Work Hours: 8

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