Data Analyst
2025-04-28T12:24:28+00:00
Finca Uganda Limited
https://cdn.greatugandajobs.com/jsjobsdata/data/employer/comp_1217/logo/finca.png
https://finca.ug/
FULL_TIME
Kampala
Kampala
00256
Uganda
Financial Services
Management
2025-05-12T17:00:00+00:00
Uganda
8
Application Deadline: May 12, 2025
Job Summary:
Finca Uganda, a leading financial institution committed to building tomorrow together, is seeking a skilled Data Analyst to join our team. The Data Analyst will leverage data-driven expertise to provide actionable insights, support decision-making, and enhance Finca Uganda’s operations in microfinance, credit risk, and mobile banking. This role is ideal for a detail-oriented professional with a passion for data analysis and experience in financial services.
Key Responsibilities:
- Collect, clean, and analyze large datasets to identify trends, patterns, and insights that support business objectives.
- Develop and maintain reports, dashboards, and visualizations to communicate data findings to stakeholders.
- Support strategic decision-making by providing data-driven recommendations on credit risk, customer behavior, and market trends.
- Collaborate with cross-functional teams to assess business needs and design analytical solutions.
- Monitor and evaluate the performance of microfinance products, identifying areas for improvement.
- Conduct predictive and prescriptive analysis to enhance risk management and operational efficiency.
- Ensure data integrity and accuracy by implementing quality control measures and validation checks.
- Stay updated on industry trends, tools, and technologies to improve data analysis processes.
- Assist in the integration of mobile banking data to optimize customer engagement and service delivery.
- Document analytical processes, methodologies, and findings for future reference and audits.
Qualifications and Skills:
- Minimum of an Honours University Degree in Statistics, Applied Mathematics, Economics, Econometrics, Actuarial Science, Computer Science, Information Technology, Operations Research, Industrial Engineering, or other quantitative disciplines from a recognized institution.
- At least 3 years of experience as a Data Analyst, Business Intelligence Analyst, Quantitative Analyst, or Data Scientist, preferably in financial services.
- Experience within microfinance, credit risk, banking, or mobile networks is an added advantage.
- Proficiency in data analysis tools and programming languages such as SQL, Python, R, or similar.
- Strong skills in data visualization tools like Tableau, Power BI, or Excel for creating dashboards and reports.
- Excellent analytical and problem-solving skills with a keen attention to detail.
- Ability to interpret complex data and communicate findings effectively to non-technical stakeholders.
- Familiarity with statistical methods, predictive modeling, and machine learning techniques is a plus.
- Strong organizational skills to manage multiple projects and meet deadlines.
- Passion for using data to drive impact in financial inclusion and customer service.
Collect, clean, and analyze large datasets to identify trends, patterns, and insights that support business objectives. Develop and maintain reports, dashboards, and visualizations to communicate data findings to stakeholders. Support strategic decision-making by providing data-driven recommendations on credit risk, customer behavior, and market trends. Collaborate with cross-functional teams to assess business needs and design analytical solutions. Monitor and evaluate the performance of microfinance products, identifying areas for improvement. Conduct predictive and prescriptive analysis to enhance risk management and operational efficiency. Ensure data integrity and accuracy by implementing quality control measures and validation checks. Stay updated on industry trends, tools, and technologies to improve data analysis processes. Assist in the integration of mobile banking data to optimize customer engagement and service delivery. Document analytical processes, methodologies, and findings for future reference and audits.
Minimum of an Honours University Degree in Statistics, Applied Mathematics, Economics, Econometrics, Actuarial Science, Computer Science, Information Technology, Operations Research, Industrial Engineering, or other quantitative disciplines from a recognized institution. At least 3 years of experience as a Data Analyst, Business Intelligence Analyst, Quantitative Analyst, or Data Scientist, preferably in financial services. Experience within microfinance, credit risk, banking, or mobile networks is an added advantage. Proficiency in data analysis tools and programming languages such as SQL, Python, R, or similar. Strong skills in data visualization tools like Tableau, Power BI, or Excel for creating dashboards and reports. Excellent analytical and problem-solving skills with a keen attention to detail. Ability to interpret complex data and communicate findings effectively to non-technical stakeholders. Familiarity with statistical methods, predictive modeling, and machine learning techniques is a plus. Strong organizational skills to manage multiple projects and meet deadlines. Passion for using data to drive impact in financial inclusion and customer service.
Minimum of an Honours University Degree in Statistics, Applied Mathematics, Economics, Econometrics, Actuarial Science, Computer Science, Information Technology, Operations Research, Industrial Engineering, or other quantitative disciplines from a recognized institution. At least 3 years of experience as a Data Analyst, Business Intelligence Analyst, Quantitative Analyst, or Data Scientist, preferably in financial services. Experience within microfinance, credit risk, banking, or mobile networks is an added advantage. Proficiency in data analysis tools and programming languages such as SQL, Python, R, or similar. Strong skills in data visualization tools like Tableau, Power BI, or Excel for creating dashboards and reports. Excellent analytical and problem-solving skills with a keen attention to detail. Ability to interpret complex data and communicate findings effectively to non-technical stakeholders. Familiarity with statistical methods, predictive modeling, and machine learning techniques is a plus. Strong organizational skills to manage multiple projects and meet deadlines. Passion for using data to drive impact in financial inclusion and customer service.
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