<p><b>What role you will play in team:</b> You will be a vital member of our team using cutting-edge machine learning techniques to improve fraud detection and risk management.</p><p><b>What you will do:</b> Develop and implement machine learning models to identify fraudulent transactions.  This involves large-scale data processing and model deployment.</p><p><b>Key responsibility:</b><ul><li>Develop and deploy machine learning models for fraud detection.</li><li>Process and analyze large datasets of financial transactions.</li><li>Evaluate model performance and make necessary adjustments.</li><li>Collaborate with engineers to integrate models into production systems.</li><li>Stay abreast of the latest advancements in fraud detection techniques.</li><li>Ensure compliance with regulations.</li></ul></p><p><b>Required Qualification and Skills:</b><ul><li>Master's degree in Computer Science, Statistics, or a related field.</li><li>3-5 years of experience in data science or machine learning.</li><li>Proficiency in Python or R.</li><li>Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.</li><li>Experience with big data technologies (Hadoop, Spark).</li><li>Understanding of financial markets and risk management.</li></ul></p><p><b>Benefits Included:</b><ul><li>Competitive salary and benefits package.</li><li>Opportunities for career growth and development.</li><li>Work on challenging and impactful projects.</li><li>Collaborative and supportive team environment.</li><li>Global career opportunities.</li></ul></p><p><b>A Day in the Life:</b> You will start your day with reviewing model performance metrics and then move to developing and refining machine learning models. You'll work closely with engineers for deployment and will regularly monitor model performance.</p>