<p><strong>What role you will play in team:</strong> You will contribute to a team focused on leveraging data science to improve risk management, fraud detection, and operational efficiency within the financial sector.</p><p><strong>What you will do:</strong> You will build and deploy predictive models, perform statistical analysis, and develop data-driven insights to support business decisions.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning models for risk management and fraud detection.</li><li>Analyze large financial datasets using statistical techniques.</li><li>Communicate findings to both technical and non-technical stakeholders.</li><li>Collaborate with engineers, risk managers, and other business units.</li><li>Stay updated on advancements in data science and regulatory compliance.</li><li>Develop and maintain data pipelines and infrastructure.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree or PhD in a quantitative field (e.g., statistics, mathematics, finance).</li><li>Proficiency in programming languages such as Python or R.</li><li>Experience with machine learning algorithms and techniques.</li><li>Strong analytical and problem-solving skills.</li><li>Excellent communication and presentation skills.</li><li>Knowledge of financial markets and regulatory compliance.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and comprehensive benefits.</li><li>Opportunities for career advancement and professional development.</li><li>A collaborative and supportive work environment within a leading financial institution.</li><li>Exposure to cutting-edge technologies in the financial sector.</li><li>Opportunities for global collaboration.</li></ul></p><p><strong>A Day in the Life:</strong> A typical day involves data exploration, model building, algorithm refinement, and collaborating with teams to deploy and monitor models within the firm's infrastructure.</p>