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Interpreting credit bureau and internal data for policy and pricing strategies in the lending industry. 3 years financial services analytics experience and quantitative Bachelor's degree required. Flexible working arrangements.
Requirements
- Minimum 3 years experience in lending industry
- Interest in developing career in credit risk analytics and statistical modelling within banking sector
- Bachelor's degree in Mathematics, Statistics, Economics, Physics, Computer Science, Engineering, or related quantitative discipline
- Master's degree preferred
- Minimum 3 years experience in analytics, data science, data analysis, or lending/credit assessment within financial services
- Previous experience with unsecured lender (bank, fintech, or similar credit provider)
- Strong analytical and problem-solving abilities
- Excellent attention to detail
- Proficiency in SQL
- Understanding of statistical analysis techniques
- Understanding of data modelling methodologies
- Experience or strong interest in predictive modelling
- Logistic regression knowledge advantageous
- Excellent written and verbal communication skills
- Ability to translate complex data into actionable business insights
- Strong presentation skills
- Experience communicating to diverse audiences
- Ability to work effectively in fast-paced environments
- Ability to manage multiple priorities
- Programming experience in Python or R
- Experience with data visualisation tools
- Understanding of machine learning techniques applied to credit risk
Tasks
- Collect and analyze data from internal systems
- Collect and analyze data from Credit Bureaus
- Interpret data to identify trends, patterns, and opportunities
- Inform credit policy, limits, and pricing strategies
- Develop and maintain statistical models
- Develop and maintain credit risk scorecards
- Develop and maintain credit risk assessment tools
- Provide clear insights and recommendations to stakeholders
- Support informed business decisions
- Support business growth
- Collaborate with decision sciences and analytics teams
- Work with cross-functional teams globally
- Present complex analytical findings
- Communicate findings to technical and non-technical audiences
- Prepare clear presentations and reports
- Develop clear data visualizations
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- SQL
- Python
- R
Benefits
Competitive Pay
- Competitive salary
Learning & Development
- Professional development
- Training opportunities
Informal Culture
- Collaborative and inclusive work environment
Flexible Working
- Flexible working arrangements
Career Advancement
- Career progression opportunities
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Interpreting credit bureau and internal data for policy and pricing strategies in the lending industry. 3 years financial services analytics experience and quantitative Bachelor's degree required. Flexible working arrangements.
Requirements
- Minimum 3 years experience in lending industry
- Interest in developing career in credit risk analytics and statistical modelling within banking sector
- Bachelor's degree in Mathematics, Statistics, Economics, Physics, Computer Science, Engineering, or related quantitative discipline
- Master's degree preferred
- Minimum 3 years experience in analytics, data science, data analysis, or lending/credit assessment within financial services
- Previous experience with unsecured lender (bank, fintech, or similar credit provider)
- Strong analytical and problem-solving abilities
- Excellent attention to detail
- Proficiency in SQL
- Understanding of statistical analysis techniques
- Understanding of data modelling methodologies
- Experience or strong interest in predictive modelling
- Logistic regression knowledge advantageous
- Excellent written and verbal communication skills
- Ability to translate complex data into actionable business insights
- Strong presentation skills
- Experience communicating to diverse audiences
- Ability to work effectively in fast-paced environments
- Ability to manage multiple priorities
- Programming experience in Python or R
- Experience with data visualisation tools
- Understanding of machine learning techniques applied to credit risk
Tasks
- Collect and analyze data from internal systems
- Collect and analyze data from Credit Bureaus
- Interpret data to identify trends, patterns, and opportunities
- Inform credit policy, limits, and pricing strategies
- Develop and maintain statistical models
- Develop and maintain credit risk scorecards
- Develop and maintain credit risk assessment tools
- Provide clear insights and recommendations to stakeholders
- Support informed business decisions
- Support business growth
- Collaborate with decision sciences and analytics teams
- Work with cross-functional teams globally
- Present complex analytical findings
- Communicate findings to technical and non-technical audiences
- Prepare clear presentations and reports
- Develop clear data visualizations
Work Experience
- 3 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- SQL
- Python
- R
Benefits
Competitive Pay
- Competitive salary
Learning & Development
- Professional development
- Training opportunities
Informal Culture
- Collaborative and inclusive work environment
Flexible Working
- Flexible working arrangements
Career Advancement
- Career progression opportunities
About the Company
TF Bank
Industry
FinancialServices
Description
The company is a fast-growing digital bank and a pan-European card and payment platform, developing simple and flexible payment and financing solutions.
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