Credit Risk Modelling Specialist

Company Overview

[Company name] is a leading organization in the financial services industry, focused on leveraging data analytics to enhance risk management strategies and decision-making processes.

Job Summary

The Credit Risk Modelling Specialist will be responsible for developing advanced predictive models and conducting deep-dive analyses to identify trends and insights that directly impact business strategies. This role requires a deep understanding of statistical methods and the ability to communicate findings effectively to stakeholders.

Responsibilities

• Understand business problems and translate them into statistical analyses.
• Decide on the best modeling and analysis techniques, providing actionable insights and model algorithms to the business.
• Data Extraction: Extract data from appropriate sources, requiring knowledge of databases.
• Data Processing: Perform complex data processing, including merging, sorting, and data transformations.
• Profiling and Analysis: Utilize insights and techniques such as data visualization and statistical tests to identify risk segments and behavioral trends.
• Model Development: Apply statistical modeling and machine learning techniques to identify drivers of business metrics and validate models.
• Model Scoring: Integrate developed models into the scoring process and adjust models based on feedback.
• Communication: Collaborate with team professionals to gather requirements for effective model development and implementation.

Qualifications

• Education: Bachelor's or Master's Degree in Statistics, Data Science, or related field is preferred.
• Experience: Minimum of 5 years in Credit Risk Modelling and Financial Risk Modelling.
• Statistical Tools: Extensive experience with statistical tools such as R, Python, VBA, and Excel.
• Statistical Techniques: Proficient in Univariate and Multivariate Regression, Time Series Forecasting, Logistic Regression, Decision Trees, etc.
• Data Handling: Strong ability to extract and prepare data from databases for modeling.
• Model Development: Experience in developing risk scorecards and predictive models.
• Analytical Skills: Solid understanding of machine learning algorithms and techniques.

Preferred Skills

• Familiarity with advanced statistical methods, including Non-Parametric Methods, Survival Analysis, and Boosting Techniques.
• Experience in working with data visualization tools.

Experience

• Minimum of 5 years in a relevant role focused on credit risk and financial risk modeling.

Environment

A dynamic and collaborative work environment that fosters innovation and analytical thinking. Work may be carried out in an office setting or remotely depending on the company's policies.

Salary

Salary details are not specified.

Growth Opportunities

Opportunities for professional growth through involvement in advanced analytics projects and potential leadership roles in the data science or risk management teams.

Benefits

• [List of benefits not specified; please specify if applicable.]