Engineer, Data – FLYHUB Standard Bank

To harness the power of data, make informed decisions, promote innovations, and achieve a competitive advantage in today’s data driven business landscape. To collaborate with senior management and other stakeholders to define our data intelligence strategy, lead a team of data professionals, oversee data analysis, engage with key stakeholders, and manage data intelligence technologies and tools. To apply the latest Data Science techniques to unique data assets while collaborating directly with business and any other stakeholder to drive the data-led transformation of business.
• Stays abreast of robotic process automation / Artificial Intelligence / machine learning developments and advise relevant stakeholders where necessary.
Evaluate, implement, and manage data intelligence technologies and tools, including data visualization software (Quicksight, Tableau and PowerBI), data analytics platforms, and data management systems. Stay updated on emerging technologies (AWS, Azure and Google) and trends in the data intelligence field to ensure that Flyhub remains at the forefront of innovation.
Guide in the analysis of large and complex datasets to extract meaningful insights and drive data-informed decision-making.
• Support in data analysis, data quality and other data requirement as may be determined by any given project.
Provide guidance, mentorship, and support to ensure the portfolio’s success.
• Manage tasks, manage workloads, and foster a collaborative and innovative work environment.
Work with the Architects and Operations manager as well as the Data privacy officers to develop policies and standards that need to be put in place to ensure the function can be carried out effectively and efficiently by performing initial research and drafting.

Qualifications
Minimum Qualifications
Type of Qualification: First Degree
Field of Study: Information Studies in any of the following: Data Engineering, Computer Science, Software Engineering, Electrical Engineering with a bias in IT or Information Technology. Certification in Data Analytics, Data science, Machine learning and AI is an added advantage.

Experience Required
3-5 years
• Knowledge of data principles, data science theory, techniques and tools. Knowledge is Cloud analytics tools like Quicksight, Tableau and PowerBI.
• Knowledge in Python and Java script
• Hands on Analytics/AI expert experienced in delivering Analytics projects/products in the financial services domain , involving large and complex data sets- both on premise and cloud in an individual contributor capacity.
• Ability to use Data Intelligence to draw actionable insights and make persuasive recommendations to senior stakeholders across different lines of business.
Data Science, Data Analytics, Data Engineering, AI and Machine Learning

Additional Information
Behavioral Competencies:
• Generating Ideas
• Exploring Possibilities
• Documenting Facts
• Convincing People
• Meeting Timescales
• Team Working
• Valuing Individuals
• Articulating Information
• Conveying Self-Confidence
• Checking Details
• Establishing Rapport
• Following Procedures

Technical Competencies:
• AI and Machine Learning
• Documenting
• IT Applications
• Data Science, Data Analytics, Data Engineering.