<p><strong>What role you will play in team:</strong> You'll be part of a team focused on developing and implementing advanced analytical solutions to improve operational efficiency and drive strategic decision-making within the financial services industry.</p><p><strong>What you will do:</strong> You will work on a range of projects leveraging machine learning and statistical modeling techniques.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning models for various applications such as fraud detection, risk assessment, and customer segmentation.</li><li>Perform extensive data analysis and feature engineering to improve model accuracy.</li><li>Deploy models into production environments and monitor their performance.</li><li>Collaborate with engineers and business stakeholders to define project requirements and communicate findings.</li><li>Stay current with the latest advancements in data science and financial technology.</li><li>Adhere to strict regulatory guidelines and compliance standards.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree or PhD in a quantitative field (e.g., statistics, computer science, finance).</li><li>Proficiency in Python or R programming languages.</li><li>Experience with machine learning algorithms (e.g., regression, classification, clustering).</li><li>Experience with big data technologies (e.g., Hadoop, Spark) is a plus.</li><li>Strong communication and presentation skills.</li><li>Understanding of financial markets and regulations is a plus.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and benefits.</li><li>Robust training and development opportunities.</li><li>Challenging and rewarding work environment.</li><li>Opportunities for career progression within a global organization.</li><li>Health, wellness, and financial planning resources.</li></ul></p><p><strong>A Day in the Life:</strong>  A day involves collaborating with team members, developing and testing machine learning models, analyzing data, and preparing reports for stakeholders.</p>