Job Description
• Risk Analysis & Monitoring:
o Develop and maintain risk models to identify and assess potential credit, fraud, and operational risks.
o Monitor KPIs related to customer behaviour, merchant activity, and repayment trends to detect anomalies or emerging risks.
• Data Analytics:
o Conduct deep dives into large datasets to identify patterns, correlations, and trends that impact risk and business decisions.
o Build automated dashboards and reports to deliver actionable insights to key stakeholders.
• Model Development:
o Design and implement statistical and predictive models to improve credit scoring and fraud detection processes.
o Collaborate with the engineering and product teams to deploy data models into production systems.
• Collaboration:
o Work closely with the Risk, Product, Commercial and Marketing teams to develop strategies based on data insights.
o Present findings and recommendations to the leadership team.
Position Requirement
• Technical Skills:
o Strong proficiency in Python for data analysis and model development.
o Advanced knowledge of SQL for querying and manipulating large datasets.
o Experience with data visualization tools (e.g., Tableau, Power BI, or similar).
o Familiarity with machine learning techniques (classification, regression, clustering) and tools like TensorFlow, PyTorch, or Scikit-learn is a plus.
o Knowledge of statistical concepts and techniques for data interpretation.
• Analytical Skills:
o Strong problem-solving ability with a focus on actionable results.
o Experience in identifying and managing risks within a fintech, banking, or similar environment is highly desirable.
• Other Requirements:
o Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, or related field.
o 1+ years of experience in a similar role within fintech, e-commerce, or banking.
o Strong communication and presentation skills to convey complex concepts to non-technical stakeholders.
