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Engineer, Data – FLYHUB

at Stanbic Bank
Location Kampala, Uganda
Date Posted May 15, 2024
Category Banking
Engineering
Finance
Job Type Full-time
Currency UGX

Description

About US:

Stanbic Bank Uganda Limited is a subsidiary of Stanbic Africa Holdings Limited which is in turn owned by Standard Bank Group Limited (“the Group”), Africa’s leading banking and financial services group. The Standard Bank Group is the leading banking group focused on emerging markets. It is the largest African banking group ranked by assets and earnings. Stanbic Bank Uganda Limited is the largest bank in Uganda by assets and market capitalization. It offers a full range of banking services through two business units; Personal and Business Banking (PBB), and Corporate and Investment Banking (CIB).

 

Job Summary:  The Engineer, Data – FLYHUB will 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.

 

Key Duties and Responsibilities:

  • 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, Skills and Experience:

  • The applicant for the Stanbic Bank job must hold a First Degree in 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.
  • Three to five years of related work experience
  • 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

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.

 

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