Senior Data Modeler
Senior Data Modeler
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1 Vacancy
Job Description
Job description
Essential Duties and Responsibilities Handle the delivery of multiple complex analytics projects to clients from inception to completion Open to handson modelling work Manage (small) projects to achieve milestones /manage& motivate project team to ensure quality deliverables Mentor and coach junior team members in model development process Drive high standards of customer service and proactive client communication throughout the project term Proactively communicate project status and deliverables through the life of the project Ensure issues raised by the client are resolved in a timely and efficient manner Prepare and deliver structured model development/validation training courses to the SEA clients Flexible to travel to client locations on short notice for project delivery(30%) Knowledge & Experience Up to 05 years experience in credit risk modelling across customer life cycle Expert in any two analytical programing languages SASPython and R Comfortable with large data sets Thorough understanding of the Application/Behaviour/Collection scorecard development process. Thorough knowledge of the use and application of analytical methodologies Linier Regression Logistic Regression etc Thorough understanding of segmentation techniques CHAID CART etc. Good understanding of PD EAD and LGD model development & validation process. Significant experience of statistical / analytics project work Experience of working in a financial services environment or Modelling department of International Banks Strong analytical skills. Excellent communication and interpersonal skills. Qualifications Degree or equivalent standard with a high numeric content e.g. Mathematics Statistics Operational Research Economics Physical Sciences. Graduate calibre with formal project management skills/qualifications.
Qualifications :
Qualifications
- Handson experience processing and analyzing data by using tools such as Python R etc. Good applied statistics skills such as distributions statistical testing regression etc. Good understanding of model predictive model development (such as Credit risk models Fraud models etc.). A strong understanding of machine learning techniques and algorithms such as Gradient Boost KNN etc. Knowledge of different modelling frameworks like Linear Regression Logistic Regression MultipleRegression LOGIT PROBIT time series modelling CHAID CART etc. Understanding of decisioning and portfolio management in banking and financial services would be addedadvantage
Additional Information :
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Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
