RISK ANALYTICS OFFICER

The Analytics Officer Is Set To Initiate And Apply Data Science Best Practices For Developing Program Logics And/or Conducting Preliminary Tests And Analysis For Activities Such As But Not Limited To The Following

• Development of propensity/predictive models, credit risk models and business studies.
• Integration of developed models to systems and internal processes within and outside the division.
• Performance monitoring risk models and other data tools currently implemented.
• Creation of various business dashboards, operating risk MIS and other adhoc reporting.
• Mining, processing, and transformation of data needed for above-mentioned analytics activities.
  
  

Responsibilities

• Risk Management Support: Develop, monitor and maintain Credit Risk Models, Risk MIS/Dashboard (i.e., Portfolio Dashboard, Collection Dashboard and other reports) used to effectively monitor and manage risk and minimize non-performing loans. Participates in the user acceptance test to ensure models are appropriately implemented not only within the direct system environment but also its relevant downstream environments.
• Business Decision Support: Conducts various studies and other analytics projects (descriptive/prescriptive models, segmentation analysis, etc.) that serve as tool for underwriting decisions and/or drive new insights for market expansion and/or policy refinements. Present results and insights to different stakeholders and recommendations on business initiatives that are worth pursuing.
• Service Delivery Management: Work plan and delivery schedule of all analytics projects assigned. This also includes ensuring all projects and regular tasks are deliver based on agreed timelines and business specifications.
  
  

Qualifications

• Bachelor’s Degree in Mathematical Sciences, Physics or Economics or Engineering.
• Master’s Degree in Mathematical Sciences, Physics or Economics or Engineering.
• Decision Analytics / Data Science application, preferably in retail business environments.
• Analytical Skills.
• Curious about the data and strong ability to identify unusual patterns and data variations.
• Strong ability to link data to the business problem and/business solution.
• Proficient in various data tools such as SAS, R, Phyton, Tableau and the likes.
• Advance skills in data programming and data manipulation.
• Advance knowledge statistical analysis and statistical modeling (forecasting, linear and logistic regressions, random forest, and the like).
• Proficient in various data spreadsheets and story board presentation software.
• Proficient in oral and written communication and can converse results and insights clearly to the business units.
• Regularly look for opportunities to turn ideas into action; focuses on identifying new patterns, variations, and analogies to generate new ideas.
• Results oriented and good project management skills.

The Analytics Officer Is Set To Initiate And Apply Data Science Best Practices For Developing Program Logics And/or Conducting Preliminary Tests And Analysis For Activities Such As But Not Limited To The Following

• Development of propensity/predictive models, credit risk models and business studies.
• Integration of developed models to systems and internal processes within and outside the division.
• Performance monitoring risk models and other data tools currently implemented.
• Creation of various business dashboards, operating risk MIS and other adhoc reporting.
• Mining, processing, and transformation of data needed for above-mentioned analytics activities.
  
  

Responsibilities

• Risk Management Support: Develop, monitor and maintain Credit Risk Models, Risk MIS/Dashboard (i.e., Portfolio Dashboard, Collection Dashboard and other reports) used to effectively monitor and manage risk and minimize non-performing loans. Participates in the user acceptance test to ensure models are appropriately implemented not only within the direct system environment but also its relevant downstream environments.
• Business Decision Support: Conducts various studies and other analytics projects (descriptive/prescriptive models, segmentation analysis, etc.) that serve as tool for underwriting decisions and/or drive new insights for market expansion and/or policy refinements. Present results and insights to different stakeholders and recommendations on business initiatives that are worth pursuing.
• Service Delivery Management: Work plan and delivery schedule of all analytics projects assigned. This also includes ensuring all projects and regular tasks are deliver based on agreed timelines and business specifications.
  
  

Qualifications

• Bachelor’s Degree in Mathematical Sciences, Physics or Economics or Engineering.
• Master’s Degree in Mathematical Sciences, Physics or Economics or Engineering.
• Decision Analytics / Data Science application, preferably in retail business environments.
• Analytical Skills.
• Curious about the data and strong ability to identify unusual patterns and data variations.
• Strong ability to link data to the business problem and/business solution.
• Proficient in various data tools such as SAS, R, Phyton, Tableau and the likes.
• Advance skills in data programming and data manipulation.
• Advance knowledge statistical analysis and statistical modeling (forecasting, linear and logistic regressions, random forest, and the like).
• Proficient in various data spreadsheets and story board presentation software.
• Proficient in oral and written communication and can converse results and insights clearly to the business units.
• Regularly look for opportunities to turn ideas into action; focuses on identifying new patterns, variations, and analogies to generate new ideas.
• Results oriented and good project management skills.