A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Our team helps clients navigate various analytics applications to get the most value out of their technology investment and foster confidence in their business intelligence. As part of our team, you'll help our clients implement enterprise content and data management applications that improve operational effectiveness and provide impactful data analytics and insights.

• Use feedback and reflection to develop self awareness, personal strengths and address development areas.
• Delegate to others to provide stretch opportunities, coaching them to deliver results.
• Demonstrate critical thinking and the ability to bring order to unstructured problems.
• Use a broad range of tools and techniques to extract insights from current industry or sector trends.
• Review your work and that of others for quality, accuracy and relevance.
• Know how and when to use tools available for a given situation and can explain the reasons for this choice.
• Seek and embrace opportunities which give exposure to different situations, environments and perspectives.
• Use straightforward communication, in a structured way, when influencing and connecting with others.
• Able to read situations and modify behavior to build quality relationships.
• Uphold the firm's code of ethics and business conduct.

• Econometric/statistical, machine learning, and other analytical modeling;
• Proficiency in analytical software and tools including Python, SAS, R, SQL and other applications, such as Microsoft Excel/VBA and Access;
• Retail and/or wholesale credit risk models, including underwriting scorecards, loss forecasting models, prepayment models, and/or complex discounted cash flow models;
• Statistical and machine learning techniques for analyzing financial data, including: survival analysis, time series analysis, GLM, logistic regression, XGboost, LightGBM, Random Forest, Neural Networks, decision tree analysis, and cluster analyses;
• Model documentation and/or model validation report writing;
• Thorough understanding of model risk management concepts and practices;
• Demonstrates thorough knowledge of rules and regulations, including SR11-7/OCC 11-12, SR 15-1819, CECL, IFRS9; and,
• Exhibits proven verbal and written communication skills.

• Modeling experience in the financial industry covering retail (e.g., mortgages, credit cards, auto loans) and wholesale (e.g., Commercial and Industrial, Commercial Real Estate) credit underwriting and loss forecasting models including CECL, IFRS 9 and CCAR as well as other business areas such as marketing and collections, fraud detection/scoring models.
• Expertise in multiple modeling methodologies including survival analysis, transition rate modeling, time series analysis, credit scoring, Monte Carlo simulation, Artificial Intelligence/Machine Learning techniques such as neural networks and tree based algorithms etc.; and,
• Proven verbal and written communication skills to interface effectively with modelers/validators and all levels of client management.