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Central Bank of Kenya, Equity Bank Kenya , Mogo Kenya Limited , NCBA, Old MutualProfession (Banking, microfinance, insurance)
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Industry
Aeronautics,Agriculture, fishing, forestry,Automotive,Banking, microfinance, insurance,Communications, media, radio, tv,Computers, software development and services,Construction, renovation, maintenance,Consulting, business support, auditing,Data/Research,Education, academic,Electronics,Energy, utilities, environment,Engineering, architecture,Entertainment, events,Finance & FinTech,Financial Services,Governmental,Health care, medical,Housekeeping, maintenance,Human resources, talent development, recruiting,Legal, accounting,Manufacturing,Marketing, advertising,Non-profit, social work,Outsourcing, leasing,Real estate,Restaurant, hospitality, travel,Retail, wholesale, FMCG,Security,Telecommunications,Textile, fashion,Transportation, logistics, storage,
Seniority (Banking, microfinance, insurance)
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Family Bank Kenya
Banking + 2 more
Description
The Person:
- The ideal candidate must possess the following:
Qualifications/Experience:
- Graduate degree in Computer Science, Mathematics, Physics, Statistics, Engineering, Informatics, Information Systems or another quantitative.
- Advanced working SQL knowledge and experience working with relational databases, query authoring
- (SQL) as well as working familiarity with a variety of databases
- Experience with data pipeline and workflow management tools: Luigi, Airflow, etc.
- Experience with object-oriented/object function scripting languages.
- 2-5 years’ experience in technology/data analytics
Responsibilities
- Architecture design: Envision and designing the architecture of the data platform in line with business requirements.
- Development of data related instances: Develop, customize and manage integration tools, databases, warehouses, and analytical systems.
- Data pipeline maintenance: Responsible for Maintenance and monitoring of the overall performance and stability of the system.
- Machine learning algorithm deployment: Responsible for deploying of Machine learning models to production environments. This entails, configuring data attributes, managing computing resources, setting up monitoring tools, etc.
- Manage data and meta-data: Responsible for managing the data stored and structuring it properly via database management systems.
- Any other official duty that may be allocated from time to time.
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