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Senior Credit Risk Analyst
hace 2 semanas
We are seeking a seasoned Senior Credit Risk professional with expertise in credit risk analytics and statistical modelling in the banking sector. As Senior Credit Risk Analyst, you will play a crucial role in developing credit risk analytics area in the bank.
**Key Responsibilities**:
- Collect and analyze data from various sources, including internal systems, Credit Bureaus, to identify trends, patterns, and opportunities and propose changes in credit policy or marketing activities.
- Develop and maintain statistical models e. g. scorecards for credit risk area.
- Provide actionable insights and recommendations to stakeholders based on data analysis, helping them make informed decisions and drive business growth.
- Collaborate with teams within decision and analytics area and other ones in different geographical locations.
- Effectively communicate complex analytical findings and insights to both technical and non-technical stakeholders through presentations, reports, and visualizations.
**Qualifications and Experience**:
- Bachelor's degree in a relevant field such as Mathematics, Statistics, Economics, Quantitative Methods, Computer Science or Engineering. A Master's degree is preferred.
- Minimum of 2 years of experience in analytics or a data science field.
- Experience in the financial sector is preferred, especially in retail credit risk area.
- Excellent analytical and problem-solving skills, with a strong attention to detail. Algorithmic and creative approach to solving problems.
- Proven track record of delivering impactful insights and recommendations based on data analysis.
- Fluent English to be able to collaborate with colleagues from other countries.
- Proficiency in data modelling methodologies and statistical analysis techniques.
- Practical knowledge from the UK market will be a plus.
- Knowledge of programming languages such as Python or R is preferred.
- Excellent knowledge of SQL for data extraction and manipulation.
- Experience in predictive modelling using logistic regression will be a plus.
- Good communication and presentation skills, with the ability to translate complex data into clear and actionable insights.
- Ability to work effectively in a fast-paced, dynamic environment, managing multiple priorities and meeting deadlines.
Please submit your updated CV in **English**.
