<p><strong>What role you will play in team:</strong> You'll be part of a team developing and implementing machine learning models for fraud detection within the bank's operations.</p><p><strong>What you will do:</strong> You will design, develop, and deploy machine learning models to improve the accuracy and efficiency of fraud detection systems.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning algorithms for fraud detection.</li><li>Evaluate model performance and identify areas for improvement.</li><li>Collaborate with other engineers and data scientists to build and deploy models into production.</li><li>Maintain and monitor models in production.</li><li>Stay up-to-date on the latest advances in machine learning.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree in Computer Science, Statistics, or a related field.</li><li>3-5 years of experience in machine learning engineering.</li><li>Proficiency in Python, TensorFlow, and scikit-learn.</li><li>Experience with cloud computing platforms (e.g., AWS, Azure, GCP).</li><li>Excellent problem-solving and communication skills.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and benefits package.</li><li>Opportunities for professional development.</li><li>Work from home option.</li><li>Dynamic and collaborative team environment.</li></ul></p><p><strong>A Day in the Life:</strong> A typical day involves collaborating with a team, developing algorithms, and testing model performance to ensure efficient fraud detection.</p>