Overview
Key Responsibilities:
- Extract, clean, and analyze large datasets to identify patterns and trends.
- Develop and maintain dashboards and reports to monitor business performance.
- Work with cross-functional teams to improve data accuracy and accessibility.
- Conduct deep-dive analysis on customer behavior, transactions, and engagement to improve retention and acquisition strategies
- Work with cross-functional teams to improve data accuracy and accessibility.
- Identify potential risks, anomalies, and opportunities for business growth using data.
Required skills and Qualifications:
- Education: Bachelor's or Master’s degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field.
- Minimum 1 year of domain exposure in Banking, Lending, or Fintech verticals.
- Advanced knowledge of Python for data analysis, with familiarity in EDA, feature engineering, and predictive analytics.
- Expertise in SQL for data querying and transformation.
- Mandatory experience in Tableau for building executive dashboards and visual storytelling.
Optional exposure to:
- Apache Airflow for orchestration of ETL workflows
- Cloud platforms such as AWS or GCP
- Version control tools like Git or Bitbucket
- This role will involve working on real-time data pipelines, credit risk models, and customer lifecycle analytics in a dynamic fintech environment
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