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. It also owns KCB Insurance Agency, KCB Capital, KCB Foundation and all associate companies. The holding company was set up to among other things to enhance the Group’s capacity to access unrestricted capital and also enable investment in new ventures outside banking regulations, achieve operational and strategic autonomy for the Group’s operating entities and enhance corporate governance across the Group and oversight in management of subsidiaries.
The Position
Reporting to the Head of Data and Analytics, the role holder will be responsible for the implementation of initiatives that impact business positively through the use of advanced analytics techniques such as predictive and prescriptive modelling, advanced statistical analysis, data mining, data visualization and machine learning. This role requires a blend of technical, business, interpersonal and data science skills that will be utilized to manipulate, analyze and interpret large and varied datasets resulting in insights and analytics solutions that enhance business performance.
Key Responsibilities
- Advise the business leadership team on analytics value opportunities on an ongoing basis and translate business problems into specific analytics and technology enabled solutions.
- Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions through Advanced Analytics and the use of various data mining techniques such as exploratory data analysis and statistical analysis.
- Create predictive and prescriptive advanced analytics solutions and models that will support various business initiatives and result in actionable insights and recommendations, operational decisions and ensure effective business outcomes.
- Develop and maintain user and technical documentation/manuals on business requirements (business questions and hypothesis), data sources, ETL related activities, data quality assessment, data cleansing activities, data mining analyses, models developed, reports generated and statistical solutions developed and deployed.
- Assess the effectiveness and accuracy of new data sources, data governance activities (e.g. data quality and cleansing strategies) data gathering techniques and develop processes and tools to monitor, analyze and tune model performance and data accuracy.
- Work with both structured and unstructured data including transforming of large, complex datasets into pragmatic and actionable insights.
- Utilize industry standards and methodologies such as CRISP-DM in the analysis and development of advanced analytics solutions and development of best practices for model development, data mining, management, maintenance, reporting and security.
- Drive innovation through Advance Analytics democratization initiatives such as creating awareness and assisting business in understanding the power and value of analytical approaches to decision-making, evangelizing through e-learning, training business on how to use some of the advanced analytics tools, showing them how to interpret results, insights and contribution to the organization’s strategic goals and influence their decision-making processes.
- Develop and implement strategic partnerships in the business, technology and academic field
- Stays abreast of industry and regulatory trends that may impact new and existing strategy development.
Job Requirements
For the above position, the successful applicant should have the following:
- Degree in Computer Science, Information Technology, Business, Statistics, Mathematics or equivalent from an institution recognized by CUE is required.
- Masters’ degree in Strategic Management / Business Administration or related fields is an added advantage.
- Proficiency in SQL, R, Python, Supervised and Unsupervised Machine Learning Techniques is a significant advantage.
- Proficiency in SAS, Stata, SPSS, Matlab, Big data technologies (Map/Reduce, Hadoop, Hive, Spark), Deep Learning Techniques.
- Minimum of 5 years proven performance in Data Science & Analytics.
- Experience implementing Banking/Financial Use Cases will be an added advantage.
- Broad understanding of latest Data Science, Analytics and Technology trends and their impact on business strategies and operations
- Experience in the use of Machine learning algorithms and techniques like supervised and unsupervised machine learning, clustering, neural networks, reinforcement learning, decision trees, regression, and adversarial learning.
- Expertise in querying and extracting large datasets from various sources (Relational Databases, text and pdf files, websites etc.) and visualizing/presenting data as actionable insights to stakeholders.
- Have extensive statistical analysis and/or data science experience utilizing R, Python and/or SAS in manipulating data and drawing insights from large data sets.
- Excellent team collaboration skills with the ability to work in matrix organization and influence people.
- Excellent verbal, written, and data presentation skills
- Flexible and capable of handling multiple tasks in a fast paced, high volume environment
- Have an inquisitive nature with an aptitude to diagnose and tackle analytically complex business problems.
The above position is a demanding role for which the Bank will provide a competitive remuneration package to the successful candidate.
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