<p><b>What role you will play in team:</b> You will be part of a dynamic team working on fraud detection and prevention.  You'll contribute to building and improving our machine learning models.  Collaboration and learning are key to this role.</p><p><b>What you will do:</b> You will develop and implement machine learning algorithms for fraud detection. You'll analyze large datasets to identify patterns and trends. You'll work closely with engineers to deploy your models into production.</p><p><b>Key responsibility:</b><ul><li>Develop and implement machine learning models for fraud detection.</li><li>Analyze large datasets to identify patterns and trends.</li><li>Collaborate with engineers to deploy models into production.</li><li>Work with stakeholders to understand business requirements.</li><li>Communicate findings and recommendations clearly and effectively.</li><li>Stay up-to-date with the latest advances in machine learning.</li></ul></p><p><b>Required Qualification and Skills:</b><ul><li>Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.</li><li>Proficiency in Python or R.</li><li>Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.</li><li>Strong analytical and problem-solving skills.</li><li>Excellent communication and teamwork skills.</li></ul></p><p><b>Benefits Included:</b><ul><li>Competitive salary and benefits package.</li><li>Opportunities for professional development and growth.</li><li>A collaborative and supportive work environment.</li><li>Health insurance, paid time off, and other benefits.</li></ul></p><p><b>A Day in the Life:</b>  You'll start your day by reviewing model performance metrics. You'll then collaborate with engineers to deploy model updates.  The afternoon will involve analyzing new data to identify potential fraud patterns.  You'll end your day by preparing a report summarizing your findings.</p>