DART (The Risk Data, Analytics, Reporting & Technology) is the leading risk modelling and data analytics team in Citi. We use mathematical modelling and the latest technologies to calculate risk for the largest portfolios in Citi. We use visualizations and dashboards to communicate risk to senior stakeholders. Our models and analytics ensure that the bank has adequate capital during crisis.

We are a diverse group of professionals with backgrounds in physics, engineering, finance, economics, and data science. You will work alongside experienced colleagues to further develop your analytical and quantitative skills. Your responsibilities will include building models and analytical applications to tackle real-world challenges, paving the way for a career as a risk management expert and leader.

As a successful Candidate you will be a part of Loss Forecasting Team, which is responsible for statistical models used in reserves calculation (IFRS9 & CECL) and stress testing (ICAAP, CECL and others). The role offers a huge development opportunity and exposition to local and global initiatives.

Responsibilities:

• Research, develop, and test wholesale expected credit loss models in line with IFRS9 or CECL requirements, credit loss models used for regulatory stress testing including CCAR/ICAAP and internal stress testing.

• Implement credit loss models in python or other for both model execution, testing, and analytical tools.

• Prepare detailed quantitative modeling and analysis for risk managers and senior management.

• Synthesize and communicate complex risk models and results.

• Conduct statistical analysis, quantitative modeling, and model risk controls.

• Work with risk managers, businesses, and tech to design and build models for risk capture and stress testing.

Qualifications:

• Master degree from a quantitative field (Mathematics, Physics, Computer Science, Econometrics, Statistics, Economics, Finance, etc.) is required.

• 2+ years of experience in quantitative financial modeling. Hands-on experience with the research, development, and implementation of financial models.

• Ability to apply sophisticated mathematical/analytical techniques to solve real-world problems.

• Knowledge of wholesale credit products and financial markets at a financial institution is preferred.

• Good knowledge of credit reserves calculation in line with IFRS9/CECL, bank stress testing in line with ICAAP/CCAR or PD/LGD/EAD modeling is a plus.

• Familiar with statistics packages and regression models.

• Strong programming skills in Python. Good knowledge of Linux is a plus.

• Excellent communication skills, verbal as well as written.

We offer:

• Work in a challenging area of the financial industry with one of the world's leading companies with exposure to variety of products, processes and controls.
• Cooperation with a high quality, international, multicultural, and global team.
• Work in a friendly and diversified environment, appreciating differences in style and perspective and using them to add value to decisions leading to organizational success.
• Management supporting balanced and agile work (flexible working hours, home office).
• Attractive benefits package (Benefit System, medical care, pension plan etc.).
• A chance to make a difference with various affinity networks and charity initiatives.

#LI-JB2

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Job Family Group:

Risk Management

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Job Family:

Risk Analytics, Modeling, and Validation

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Time Type:

Full time

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