Collection Data Analyst

Akulaku Group

Jakarta Pusat

Presencial

IDR 180 000 000 - 300 000 000

Tempo integral

há 6 horas
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Resumo da oferta

Akulaku Group in Jakarta Pusat is seeking a data analyst to monitor and improve the Collection process. You will drive data-driven risk insights, support regulator requests, and deliver performance analytics for collection operations.

The role requires 4+ years in data analysis, strong SQL and Excel skills, and experience with visualization tools like Superset or Power BI, along with cross-functional collaboration capabilities.

Qualificações

  • Bachelor's degree in Data Science, Information Systems, Statistics, Mathematics, Economics, or a related quantitative field.
  • Minimum 4 years of experience in a data analyst role, preferably in financial services, fintech, or collection/credit operations.
  • Strong proficiency in SQL, Excel/Google Sheets (advanced), and visualization/analytics tools such as Superset, Power BI, or Python.
  • Strong understanding of collections operations, portfolio management, delinquency metrics, and lending business processes.
  • Strong analytical thinking with the ability to draw meaningful conclusions from large datasets.
  • Able to communicate complex data clearly to both technical and non-technical audiences.
  • Strong analytical thinking, problem-solving capability, and attention to detail.
  • Comfortable managing multiple priorities in a fast-paced environment.
  • Experience working cross-functionally with business, operations, risk, and data teams in fast-paced environments.

Responsabilidades

  • Provide accurate and valuable monitoring to identify areas of improvement in the Collection process.
  • Identify any potential risk related to Collection process by data driven analysis.
  • Assist manager on delivering best practice insights to evaluate the Operation performance.
  • Calculate and evaluate the incentive calculation for each stage of Collection.
  • Assist the manager on fulfilling regulator requests such as OJK, APPI, etc.
  • Assist manager on handling channeling partners by performance, AR, and analytics.
  • Provide Daily, Weekly, Report for Collection Division performance.

Conhecimentos

SQL
Excel/Google Sheets
Visualization tools
Python
Collections operations

Formação académica

Bachelor's degree in Data Science, Information Systems, Statistics, Mathematics, Economics, or related quantitative field

Ferramentas

Superset
Power BI

Descrição da oferta de emprego

  • Provide accurate and valuable monitoring to identify areas of improvement in the Collection process.
  • Identify any potential risk related Collection process by data driven.
  • Assisting manager on delivering best practice insights to evaluate the Operation performance.
  • Calculate and evaluate the incentive calculation for each stage of Collection.
  • Assisting the manager on fulfilling the regulator request such as OJK, APPI, etc.
  • Assisting manager on handling channeling partners by performance, AR, and analytics.
  • 7. Provide Daily, Weekly, Report Report for Collection Division performance.
  • Bachelor's degree in Data Science, Information Systems, Statistics, Mathematics, Economics, or a related quantitative field
  • Minimum 4 years of experience in a data analyst role, preferably in financial services, fintech, or collection/credit operations
  • Strong proficiency in SQL, Excel/Google Sheets (advanced), and visualization/analytics tools such as Superset, Power BI, or Python
  • Strong understanding of collections operations, portfolio management, delinquency metrics, and lending business processes
  • Strong analytical thinking with the ability to draw meaningful conclusions from large datasets
  • Able to communicate complex data clearly to both technical and non-technical audiences
  • Strong analytical thinking, problem-solving capability, and attention to detail
  • Comfortable managing multiple priorities in a fast-paced environment
  • 9. Experience working cross-functionally with business, operations, risk, and data teams in fast-paced environments
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