<p><strong>What role you will play in team:</strong> You'll be part of a team building predictive models for credit risk assessment, helping to improve decision-making processes. </p><p><strong>What you will do:</strong> This involves data cleaning, feature engineering, model development, and model deployment.</p><p><strong>Key responsibility:</strong><ul><li>Develop and implement machine learning models for credit risk prediction.</li><li>Clean and prepare large datasets for model development.</li><li>Engineer features to improve model accuracy and performance.</li><li>Evaluate model performance and identify areas for improvement.</li><li>Deploy models into production environments.</li><li>Collaborate with other data scientists and stakeholders.</li></ul></p><p><strong>Required Qualification and Skills:</strong><ul><li>Master's degree in data science, statistics, or a related field.</li><li>2-4 years of experience in data science, with a focus on credit risk modeling.</li><li>Proficiency in programming languages (Python, R).</li><li>Experience with machine learning algorithms.</li><li>Experience with data visualization tools.</li><li>Strong communication and presentation skills.</li></ul></p><p><strong>Benefits Included:</strong><ul><li>Competitive salary and benefits package.</li><li>Opportunities for learning and career growth.</li><li>Collaborative and innovative work environment.</li><li>Health insurance and other welfare benefits.</li><li>Flexible work arrangements.</li><li>Opportunities for international collaborations.</li></ul></p><p><strong>A Day in the Life:</strong> You'll analyze data, develop models, and collaborate with colleagues to refine approaches and improve performance.</p>