Credit Risk Modeler

About Inetum, Positive digital flow:

Inetum is an IT services company that provides digital services and solutions and a global group that helps companies and institutions to get the most out of digital flow. The Inetum group is committed towards all these players to innovate, continue to adapt and stay ahead. With its multi-expert profile, Inetum offers its clients a unique combination of proximity, a sectorial organization and solutions of industrial quality. Operating in more than 26 countries, the Group has nearly 27,000 employees and in 2020 generated revenues of €1,965 billion.

Inetum Romania is an important player in the IT services and solutions market in our country, with over 15 years of activity. It is a stable, growing and profitable company with over 500 employees who provides IT consulting services, infrastructure and software development assistance, digital services implementation and support.

In an Agile format, our teams work on cloud initiatives, application development, business intelligence, automation and digitalization projects that contribute to the profit and evolution of our clients. The diversity of our projects offers team members the opportunity for learning and growth. The company had a turnover of 20 million EURO in 2021.

• Knowledge of Credit Risk Models – PD, EAD, and LGD, scorecards, IFRS 9, Basel II IRB approach for Credit Risk, Logistic and Linear Regression Models
• Strong experience in the credit risk model development from the scratch
• Good knowledge of R, Python (including OOP) and Statistical procedures. Knowledge of automation capabilities in R and Python
• Experience working with multiple datasets, cleaning of data and performing data analysis
• Excellent verbal and written communication abilities
• Ability to articulate ideas and develop recommendations
• Experience in working as a part of bigger teams working towards a common goal
• Proficiency in developing and giving presentations
• Strong client presentation skills
• Strong oral and written communication skills, including the ability to document analytical results suitable for audiences of all technical levels
• 5+ years of experience in Global Banks
• Strong analytical and interpersonal skills.

• The candidate needs to have a good knowledge of statistical methods and tools including logistic regression, Bayesian statistics, Markov chain process, time series analysis etc.
• Understanding of credit risk model constructs and different credit risk modeling frameworks
• Understanding of the consumption layer of the curated data, ie. Model development for credit risk models, especially IFRS9, Stress Testing and AIRB (PD, LGD and EAD models)
• Understanding of variables treatments, exclusions, transformations and data sources
• Model development experience using Python and R
• Adhoc data analysis and queries to support questions and process migration
• Prototype source data migration in established processes and production codes
• Help build competencies and develop training programs in credit risk.

The candidate will be working directly on credit risk models for a global investment bank together with the model development team of the bank and will work with them to improve the existing models. The role requires good understanding of credit risk models for wholesale portfolio, model structure, variable treatments, variable data framework and process efficiency in model development process.