Senior Data Scientist

• Advanced Data Analysis & Modeling: Uncover hidden patterns and develop insights relevant to Credit Risk using advanced statistical, quantitative, and Machine Learning methods
• Design and implement robust, scalable machine learning models
• Model Optimization & Monitoring: Optimize model performance and design automated solutions for model monitoring, including data drift detection and correction strategies
• Explainable AI for Risk: Apply advanced analytics and AI/ML methods to explain root causes for changes in pre-settlement risk, ensuring transparency and interpretability of models
• Framework Development: Develop scalable data science frameworks to enable efficient, build-once, deploy-many capabilities for various financial models
• Production Integration: Develop and integrate machine learning algorithms into production-grade applications, particularly using FastAPI, ensuring robust, performant, and maintainable solutions
• Strategic Product Contribution & Collaboration: Contribute to the full product lifecycle from ideation and requirements gathering to development, launch, and post-launch performance monitoring, partnering with senior leadership, business analysts and engineering teams to gather requirements, manage expectations, and secure alignment
• Responsible AI & Governance: Ensure all data products and analytical solutions adhere to Citi's stringent risk, compliance, and regulatory standards, including data privacy and ethical AI principles within the financial domain

• Hands-on experience in building and deploying Machine Learning solutions in a production environment
• Profound knowledge of quantitative methods, probability theory, statistics, and numerical methods
• Demonstrated MLOps expertise, encompassing model deployment, versioning, lifecycle management, and proficiency in data drift monitoring and correction
• Proven experience in a quantitative field
• Exceptional communication, presentation, and interpersonal skills, with a proven ability to influence diverse stakeholders
• Master's degree in Data Science, Computer Science, or a related quantitative field
• Proficiency in Python and relevant Machine Learning libraries (e.g. scikit-learn, PyTorch, TensorFlow, XGBoost, LightGBM, Pandas, NumPy)
• Experience with API development, specifically FastAPI, for integrating machine learning models into production systems
• Familiarity with MLOps and orchestration tools like MLflow and Apache Airflow

Exposure to the financial or credit risk industry

• Generous holiday allowance starting at 27 days plus bank holidays
• increasing with tenure
• A discretional annual performance related bonus
• Private medical insurance packages to suit your personal circumstances
• Employee Assistance Program
• Pension Plan
• Paid Parental Leave
• Special discounts for employees, family, and friends
• Access to an array of learning and development resources