Data Scientist

Data Scientist

Compasia Sdn Bhd

Data Scientist

Details of the offer

Job Description Job Brief As a Data Scientist you will conceptualize, develop and execute statistical, mathematical and econometric models for business decision making, risk assessment and strategic initiatives. You will responsible for financial planning models, fraud detection models, customer analytics, credit risk management and asset liability management. This position will also assist in addressing model validation requirements including remediation of validation findings.
Formulate, assess and implement statistical/mathematical models for credit risk management of retail loan portfolios. Utilize data mining and statistical techniques to develop analytic insights, sound hypotheses, and informed recommendations.
Conduct ad hoc quantitative analyses, modeling, or programming using DataBricks, SQL, R, or Python.
Develop propensity models using statistical methodologies and machine learning techniques to deliver the business objectives.
Assessing quality of model inputs/outputs through back testing against realized outcomes, bench marking against alternative models and other relevant tests. Recommend short- term and long-term model monitoring solutions based on the nature and tier of the model.
Oversee end to end the implementation and deployment of the modeling.
Explore new alternative data sources either through partnership or collaboration in achieving a robust modelling.
Bachelor's Degree/Post Graduate Diploma/Professional Degree in economics, mathematics, statistics, financial engineering, quantitative finance, or actuarial sciences. Doctoral degree preferred; or equivalent experience.
At least 3 years of work experience working as a model developer or model validator at a bank, financial firm or credit bureau agencies.
Knowledge of stress testing and regulatory requirements related to model risk management.
Experience with industry best practice modeling techniques and demonstrable skills in prototyping, benchmarking and empirical analysis.
Experience with credit risk models and consumer banking models preferred.
Candidate must have working knowledge of R/Python/SAS/SQL or other advanced statistical/econometric analysis software.
Ability to forge strong partnerships with business units across the bank.


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