<p><strong>What role you will play in team:</strong>  You'll contribute to building predictive models and analytical solutions to solve complex business problems within the financial services industry.</p><p><strong>What you will do:</strong> You will work with large datasets, employing statistical modeling and machine learning techniques to generate insights and recommendations.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning models for fraud detection, risk management, or other financial applications.</li><li>Perform exploratory data analysis to understand data patterns and relationships.</li><li>Build and maintain data pipelines for efficient data processing.</li><li>Communicate findings and insights effectively to stakeholders.</li><li>Collaborate with other data scientists and business units.</li><li>Stay updated with the latest advancements in data science and financial technology.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree in a quantitative field (e.g., statistics, mathematics, finance).</li><li>Proficiency in Python or R programming.</li><li>Experience with machine learning algorithms (regression, classification, clustering).</li><li>Experience with SQL and big data technologies (e.g., Hadoop, Spark).</li><li>Strong analytical and problem-solving skills.</li><li>Understanding of financial markets is a plus.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and benefits package.</li><li>Opportunities for professional development and career growth.</li><li>Work in a collaborative and challenging environment.</li><li>Employee Stock Ownership Plan (ESOP).</li><li>Health and wellness programs.</li></ul></p><p><strong>A Day in the Life:</strong> Your day involves data analysis, model building, testing, and collaboration with teams to present findings and discuss model implementation strategies.</p>