General Description 13;
Provide support on the administration of the Governance, Risk and Compliance application. Maintain the Customer Risk Ranking : Dynamic Customer Insight (DCI) System, the common risks, controls, process and organizational structure catalogs updated. Assist in the preparation of reports and presentations related to DCI, identifying interdependencies and trends. Perform quantitative analyses using statistical analysis software such as R. Support the development of projects that promote good governance and efficiencies in risk management through Corporate Compliance.
Essential Duties and Responsibilities 13;
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Validate statistical/machine learning models.
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Assessment of data source, data quality, robustness of methodology, alternative modelling approaches, model testing, model implementation, and model monitoring.
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Prepare the validation report that details the validation work and provides recommendations to assess issues encountered during the model validation activities.
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Communicate with business partner and stakeholders to understand the business needs, data limitations, etc.
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Determine the most appropriate testing for a given modeling approach.
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Utilize data wrangling/data matching/ETL techniques while programming in several scripting languages to explore a variety of data sources, gain data expertise, replicate the modeling process and develop challenger models.
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Perform code review.
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Ensure that the validation projects are completed on time.
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Ensure that validated models comply with regulatory and privacy requirements.
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Keep up:to:date with regulatory and legal requirements.
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Train and coach model developers on data governance and model validation activities.
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Present findings and recommendations to different stakeholders like model developers, business partners, Internal Audit, etc.
Minimum Education 13;
Bachelors Degree in Economy or Statistics or Mathematics
Masters Degree in Computer Engineering or Engineering
Experience 13;
At least two years of related experience.
Competencies 13;
Accountability
Analytical Discipline
Business Excellence
Change Agent
Character
Collaboration and Teamwork
Customer Centric
Self Development
Other Qualifications 13;
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Strong experience using Python, R or other programming language to manipulate data, visualize and draw insights from large data sets.
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Experience in development of models with a focus on predictive models. Knowledge of modeling techniques such as linear regression, logistic regression, survival analysis (Cox proportional hazard models), Generalized Linear Models (GLM), Robust GLM, regularization techniques (Ridge, Lasso, ElasticNet), decision tree:based models (Random Forest and GBM), cluster analysis, and Principal Component Analysis (PCA).
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Strong knowledge of a variety of machine learning techniques (SVM, decision trees, random forest, neural networks, etc.) and their real:world advantages/drawbacks.
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Knowledge of relational databases and SQL
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Knowledge of Machine Learning / statistical frameworks, such as Jupyter, AWS, Azure ML, Knime, SAS, Strata, etc
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Experience with
visualization tools such as Excel, PowerBI, Tableau,
etc.
Popular Inc., is an Equal Opportunity Employer
