Senior Decision Science Analyst

Senior Decision Science Analyst
Up to £65,000
London

I'm currently seeking a Senior or Lead Analyst for a Predictive Modelling role at an exciting financial services brand. You'll need experience developing Credit Risk Scorecards as well as strong academics and an excellent record of problem solving through data within a Financial Services environment.

Use data and apply advanced analytics to accurately predict customer defaults in a Credit Risk environment through application and behavioural Scorecard development, using both traditional and machine learning techniques. With end to end ownership, you'll need to present and defend the accuracy of these models to the credit committee as well as mentoring and leading the team. This is the perfect role for someone looking for an opportunity to learn and grow, with increased responsibility and accountability on offer!

THE ROLE

• Develop statistical models using rtraditional and machine learning techniques (logistic regression, KNN, Random Forests, XGBoost, etc.) to accurately predict Credit Risk defaults and customer behaviour across the customer life-cycle (Scorecards)
• Present your analysis and models to the Decision Committee and Stakeholders
• Dig into data and raw information through statistical analysis to discover trends and patterns that can be used to drive the lending strategy across the Credit Risk lifecyle
• Actively push the boundaries in modelling, predictive analytics and business insights to ensure the latest developments in data science and analytics are leveraged
• Develop and manage models for IFRS9 purposes (PD, LGD, EAD)

YOUR SKILLS AND EXPERIENCE

The successful candidate will likely have the following skills and experience:

• Master degree (preferred) in a STEM or similar discipline
• Previous experience developing predictive models or applying machine learning algorithms withina consumer Credit Risk setting (Credit RIsk Scorecards)
• Proven stakeholder management experience
• Experience managing databases with SQL and using statistical computing languages R, Python or SAS (some not all of these are required)

HOW TO APPLY

Email your CV or use the apply feature on this page

KEYWORDS

Credit Risk Analytics, Credit Risk Models, Basel, AIRB, Scorecards, Decision Science, Machine Learning, Data Science
SAS, SQL, PD, LGD, EAD, IFRS9, Logistic Regression, Decision Tree, Probability of Default, Exposure of Default, Loss Given Default