Analyst; Card Finance & Data Science job at NMB Bank
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Analyst; Card Finance & Data Science (1 Position(s))
2025-04-28T16:40:44+00:00
NMB Bank
https://cdn.greattanzaniajobs.com/jsjobsdata/data/employer/comp_5940/logo/NMB%20Bank%20.jpeg
FULL_TIME
 
Dar es Salaam
Dar es Salaam
00000
Tanzania
Banking
Commercial Banks
TZS
 
MONTH
2025-05-12T17:00:00+00:00
 
Tanzania
8

Job Purpose:

Responsible for performing a combination of statistical analysis, machine learning, data visualization, and programming skills to extract valuable information from data, as well as design and implement predictive models or intelligent algorithms to better understand the drivers of Card Business performance and enable improved management decision-making.

Main Responsibilities:

  • Create detailed card business dashboards to help assess department performance as well as unit performances and ensure accuracy of dashboard.
  • Preparation of Card Business presentations, extracting key insights from data, translate complex analysis into understandable visuals, and present findings in a compelling narrative that aligns with business objectives, and allowing decision-makers to grasp the implications of the data and make informed choices
  • Manage the life cycle of card data integration, data extraction, data transformation, data loading, report creation and operational analytics into enterprise data environment.
  • Analysis of customer behaviour to identify new sources of revenue, identify need for various campaigns/royalty programs based on behaviour and card usage (in depth analysis on Active/Dormancy for cardholders).
  • Monitor internal accounts to follow up targeted cards income and to identify abnormal losses and expenses.
  • Verified data integrity and accuracy to enable business units to make correct business decisions.
  • Ensure high availability (95) of Card Business reports by proactively scheduling alerts of system failures and working with support team to make sure issues are resolved within agreed SLAs.
  • Create in depth analytical reports to help improve efficiency and recommend changes in business units based on management goals in areas such as process automation, cost cutting etc.
  • Help in improving business processes and operational efficiency based on in depth analysis performed in different areas/units.
  • Check accuracy of data input by branches for deposits on credit/prepaid cards accounts and make appropriate adjustments according to internal procedures and guidelines.
  • Perform data analysis of networks fees, cards revenues and expenses.

Knowledge and Skills:

  • Understanding of Banking operations and scheme card products.
  • Experience in data science, machine learning and deployment of developed solutions.
  • Business analysis and requirements gathering.
  • Reproducible coding experience
  • Working with databases of all kinds
  • Experience in at least one Machine Learning language
  • Working with multiple teams to deliver predictive models into a production environment
  • Communication, Interpersonal & Relationship management Skills
  • Coordination skills and proper planning
  • Team player, working effectively within a team
  • Ability to prioritize, and meet deadlines
  • Stakeholder management at Executive and senior management level.
  • Critical thinking and decision-making skills

Qualifications and Experience:

  • University Degree in Data Science, Computer Science, Accounting or any relevant field.
  • A minimum of 2 years' Banking experience preferably in Card Business
  • Relevant experience in ICT

Create detailed card business dashboards to help assess department performance as well as unit performances and ensure accuracy of dashboard. Preparation of Card Business presentations, extracting key insights from data, translate complex analysis into understandable visuals, and present findings in a compelling narrative that aligns with business objectives, and allowing decision-makers to grasp the implications of the data and make informed choices Manage the life cycle of card data integration, data extraction, data transformation, data loading, report creation and operational analytics into enterprise data environment. Analysis of customer behaviour to identify new sources of revenue, identify need for various campaigns/royalty programs based on behaviour and card usage (in depth analysis on Active/Dormancy for cardholders). Monitor internal accounts to follow up targeted cards income and to identify abnormal losses and expenses. Verified data integrity and accuracy to enable business units to make correct business decisions. Ensure high availability (95) of Card Business reports by proactively scheduling alerts of system failures and working with support team to make sure issues are resolved within agreed SLAs. Create in depth analytical reports to help improve efficiency and recommend changes in business units based on management goals in areas such as process automation, cost cutting etc. Help in improving business processes and operational efficiency based on in depth analysis performed in different areas/units. Check accuracy of data input by branches for deposits on credit/prepaid cards accounts and make appropriate adjustments according to internal procedures and guidelines. Perform data analysis of networks fees, cards revenues and expenses.
University Degree in Data Science, Computer Science, Accounting or any relevant field. A minimum of 2 years' Banking experience preferably in Card Business Relevant experience in ICT
Understanding of Banking operations and scheme card products. Experience in data science, machine learning and deployment of developed solutions. Business analysis and requirements gathering. Reproducible coding experience Working with databases of all kinds Experience in at least one Machine Learning language Working with multiple teams to deliver predictive models into a production environment Communication, Interpersonal & Relationship management Skills Coordination skills and proper planning Team player, working effectively within a team Ability to prioritize, and meet deadlines Stakeholder management at Executive and senior management level. Critical thinking and decision-making skills
bachelor degree
24
JOB-680faf8c8d5ee

Vacancy title:
Analyst; Card Finance & Data Science 

[Type: FULL_TIME, Industry: Banking, Category: Commercial Banks]

Jobs at:
NMB Bank

Deadline of this Job:
Monday, May 12 2025

Duty Station:
Dar es Salaam | Dar es Salaam | Tanzania

Summary
Date Posted: Monday, April 28 2025, Base Salary: Not Disclosed

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JOB DETAILS:

Job Purpose:

Responsible for performing a combination of statistical analysis, machine learning, data visualization, and programming skills to extract valuable information from data, as well as design and implement predictive models or intelligent algorithms to better understand the drivers of Card Business performance and enable improved management decision-making.

Main Responsibilities:

  • Create detailed card business dashboards to help assess department performance as well as unit performances and ensure accuracy of dashboard.
  • Preparation of Card Business presentations, extracting key insights from data, translate complex analysis into understandable visuals, and present findings in a compelling narrative that aligns with business objectives, and allowing decision-makers to grasp the implications of the data and make informed choices
  • Manage the life cycle of card data integration, data extraction, data transformation, data loading, report creation and operational analytics into enterprise data environment.
  • Analysis of customer behaviour to identify new sources of revenue, identify need for various campaigns/royalty programs based on behaviour and card usage (in depth analysis on Active/Dormancy for cardholders).
  • Monitor internal accounts to follow up targeted cards income and to identify abnormal losses and expenses.
  • Verified data integrity and accuracy to enable business units to make correct business decisions.
  • Ensure high availability (95) of Card Business reports by proactively scheduling alerts of system failures and working with support team to make sure issues are resolved within agreed SLAs.
  • Create in depth analytical reports to help improve efficiency and recommend changes in business units based on management goals in areas such as process automation, cost cutting etc.
  • Help in improving business processes and operational efficiency based on in depth analysis performed in different areas/units.
  • Check accuracy of data input by branches for deposits on credit/prepaid cards accounts and make appropriate adjustments according to internal procedures and guidelines.
  • Perform data analysis of networks fees, cards revenues and expenses.

Knowledge and Skills:

  • Understanding of Banking operations and scheme card products.
  • Experience in data science, machine learning and deployment of developed solutions.
  • Business analysis and requirements gathering.
  • Reproducible coding experience
  • Working with databases of all kinds
  • Experience in at least one Machine Learning language
  • Working with multiple teams to deliver predictive models into a production environment
  • Communication, Interpersonal & Relationship management Skills
  • Coordination skills and proper planning
  • Team player, working effectively within a team
  • Ability to prioritize, and meet deadlines
  • Stakeholder management at Executive and senior management level.
  • Critical thinking and decision-making skills

Qualifications and Experience:

  • University Degree in Data Science, Computer Science, Accounting or any relevant field.
  • A minimum of 2 years' Banking experience preferably in Card Business
  • Relevant experience in ICT

 

Work Hours: 8

Experience in Months: 24

Level of Education: bachelor degree

Job application procedure

Interested and qualified? click here

 

All Jobs | QUICK ALERT SUBSCRIPTION

Job Info
Job Category: Banking/ Finance jobs in Tanzania
Job Type: Full-time
Deadline of this Job: Monday, May 12 2025
Duty Station: Dar es Salaam | Dar es Salaam | Tanzania
Posted: 28-04-2025
No of Jobs: 1
Start Publishing: 28-04-2025
Stop Publishing (Put date of 2030): 28-04-2066
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