Quantitative Modelling Analyst

2 weeks ago

London, United Kingdom Harnham Full time

**Quantitative Modelling Analyst**
**Up to £55,000**
**Leeds**

I'm currently seeking a Senior Analyst for a Predictive Modelling and Advanced Analytics role at an exciting financial services brand. If you are a bright Analyst with strong academics and strong modelling background then this could be the challenge you'vebeen looking for.

**THE ROLE**
- Use machine learning and advanced analytical techniques (Monte Carlo Simulations, Bayesian Statistics, Logistic Regression, Random Forests, KNN, XGBoost, etc.) to accurately predict and value Credit Risk and increase profits
- Develop predictive models, e.g. Scorecards, using statistical tools and techniques to increase efficiency and profitability across international markets
- Present and explain your analysis, valuations and predictions to the Decision Committee and Stakeholders
- Dig into data and raw information through statistical analysis to discover trends and patterns that can be used to extract valuable business insights.
- Actively push the boundaries in modelling, predictive analytics and business insights to ensure the latest developments in data science and analytics are leveraged

**YOUR SKILLS AND EXPERIENCE**:

- Master degree (preferred) in a STEM or similar discipline
- Previous experience in developing predictive models in a financial or pricing environment
- Proven stakeholder management examples
- Experience managing databases with SQL
- Experience in using statistical computing languages R, Python or SAS to manipulate data and draw insights from those data sets
- Experience working in a data-driven or quantitative role within financial services, ideally within Credit Risk
- Strong communicator with fluency in English (European languages an advantage)

**HOW TO APPLY**:
**KEYWORDS**:
Credit Risk Analytics, Credit Risk Models, Basel, AIRB, Scorecards, Decision Science, Machine Learning, Data Science
SAS, SQL, PD, LGD, EAD, IFRS9, Logistic Regression, Decision Tree, Monte Carlo Simulations, Bayesian Statistics, Logistic Regression, Random Forests, KNN, XGBoost

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