<p><b>What role you will play in team:</b> You will be part of a team developing and implementing machine learning models for fraud detection and risk management in the financial services industry.</p><p><b>What you will do:</b>  Develop, test, and deploy machine learning models to improve fraud detection and risk assessment capabilities.</p><p><b>Key responsibility:</b><ul><li>Develop and implement machine learning models for fraud detection and risk management.</li><li>Clean and preprocess large datasets.</li><li>Engineer features to improve model performance.</li><li>Evaluate model performance and identify areas for improvement.</li><li>Deploy models into production environments.</li><li>Collaborate with engineers and product managers.</li></ul></p><p><b>Required Qualification and Skills:</b><ul><li>Master's degree in Data Science, Statistics, or a related field.</li><li>Proficiency in Python or R programming languages.</li><li>Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.</li><li>Strong understanding of statistical modeling and machine learning techniques.</li><li>Experience with financial data is a plus.</li></ul></p><p><b>Benefits Included:</b><ul><li>Competitive salary and benefits package.</li><li>Opportunities for professional development.</li><li>Collaborative and supportive work environment.</li></ul></p><p><b>A Day in the Life:</b>  A typical day might involve data cleaning, model training, and performance evaluation, followed by collaboration with team members to improve model accuracy.</p>