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Modeler

  • Ho Chi Minh (District 4)
  • Experienced (Non - Manager)
  • Permanent
  • College
  • 1 - 2 Years
  • Negotiable
  • Banking, Financial Institution Division, Finance / Investment, Risk Division, Statistics
  • Unlimited

Job Benefit

  • Insurance
  • Travel opportunities
  • Allowances
  • Incentive bonus
  • Training & Development
  • Salary review
  • Business Expense

Job Description

  • Cooperate actively with model providers to develop, implement, test and validate the Credit Scoring Models, include Application Scoring System, Behavior Scoring System, Collection Scoring System, Propensity Scoring System, etc.
  • Apply the results of all Credit Scoring Systems to all matter of the business, if possible, to the entire consumer credit life cycle, including underwritng, x-sales and topup, debt collections, etc.
  • Continuously analyze the effectiveness of models to optimize the application of all of the scoring systems to enhance credit portfolio quality and keep portfolio heathy and sustainable.
  • Cooperate actively on technical level with IT and data warehouse teams.
  • Provide input to Portfolio Quality Review meetings

Job Requirement

Qualification & Experience

  • Min. 1 years of experience in data science related job in an credit institution maintaining retail customer data.
  • Experience of risk management practices within the Vietnam banking / consumer finance industry and familiarity with credit risk exposure calculation methodologies & tools would be desirable but not essential. 

Knowledge & Skills

  • Good knowledge and experience in business statistics, preferaly, consumer finance industry. 
  • Experience in Data Profiling and Data Cleansing.
  • Working knowledge of ETL technologies and associated implementation methodologies.
  • Strong SQL skills to support analysis of data.
  • Excellent interpersonal skills in dealing with key stakeholders.
  • A track record of delivering to aggressive deadlines.
  • Highly self-motivated.
  • Enthusiastic in detail of data and numbers
  • Fluent in English, both verbal and written
  • Experience in Data Profiling and Data Cleansing -->  Experience in Data Profiling and Data Cleansing, Exploratory, Inferential Statistics, Modelling & Prediction. .

 

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