Job Description

Job Title: Senior Risk Modeller – CreditRisk, Loss Forecasting and Portfolio Analytics

About Straive:

Straive is a market leading Content andData Technology company providing data services, subject matter expertise,& technology solutions to multiple domains. Data Analytics & AlSolutions, Data Al Powered Operations and Education & Learning form thecore pillars of the company’s long-term vision. The company is a specializedsolutions provider to business information providers in finance, insurance,legal, real estate, life sciences and logistics. Straive continues to be theleading content services provider to research and education publishers. DataAnalytics & Al Services: Our Data Solutions business has become critical toour client's success. We use technology and Al with human experts-in loop tocreate data assets that our clients use to power their data products and theirend customers' workflows. As our clients expect us to become their future fitAnalytics and Al partner, they look to us for help in building data analyticsand Al enterprise capabilities for them. With a client-base scoping 30 countriesworldwide, Straive’s multi-geographical resource pool is strategically locatedin eight countries - India, Philippines, USA, Nicaragua, Vietnam, UnitedKingdom, and the company headquarters in Singapore.

Website: https://www.straive.com/

Job Summary:

As a Senior Risk Modeller specializing inCredit Risk, loss forecasting, you'll develop and maintain models to predictcredit losses, manage credit risk, analyse their drivers, and stress-testportfolios, while communicating findings to both technical and non-stakeholdersand collaborating with other teams to improve forecasting accuracy and credit riskmanagement.

·        Model Development &Validation: Develop and validate loss forecastingmodels, including those for credit risk, CECL, and other areas.

·        Data Analysis &Interpretation: Analyse large datasets, identifykey drivers of loss, and interpret model results to inform decision-making.

·        Stress Testing: Conduct stress tests ofcredit portfolios to assess the impact of changing economic and businessconditions.

·        Communication & Collaboration: Communicatefindings to both technical and non-technical audiences, including seniormanagement and other stakeholders.

·        Documentation & Reporting: Maintaincomprehensive documentation for loss forecasting policies and procedures.

·        Technical Skills: Proficiency in statistical modelling techniques, programminglanguages (e.g., Python, SQL), and data analysis tools.

·        Industry Knowledge: Strong understandingof financial regulations, risk management principles, and industry bestpractices.

·        Leadership & Teamwork: Ability tolead projects, mentor junior team members, and collaborate effectively withcross-functional teams.

·        Problem Solving: Identify and addressissues related to model performance, data quality, and business needs.

·        Adaptability: Remain current withevolving risk management practices, regulatory changes, and modellingtechniques.

Qualifications:

·        Master’s or Ph.D. in aquantitative field such as Statistics, Mathematics, Economics, Finance, DataScience, or a related discipline.

·        8+ years of experience in riskmodelling, credit risk analytics, loss forecasting, or a related area withinbanking, financial services, or consulting.

·        Hands-on experience developingand validating credit risk models, including CECL, IFRS 9, stress testing, andregulatory models.

·        Experience working with largefinancial datasets and applying statistical/econometric techniques for riskanalysis.

·        Strong proficiency inprogramming languages such as Python, R, SQL, SAS for model development anddata analysis.

·        Expertise in machine learningand statistical modelling techniques, including logistic regression, timeseries forecasting, survival analysis, and decision trees.

·        Strong understanding of creditrisk concepts, financial regulations (e.g., CECL, Basel II/III, IFRS 9), andstress testing frameworks.

·        Knowledge of banking products,loan portfolios, and macroeconomic factors affecting credit losses.

·        Excellent communication andstakeholder management skills, with the ability to present complex findings tonon-technical audiences.

·        Strong problem-solvingabilities to address data quality issues, improve model performance, and alignrisk strategies with business objectives.

·        Leadership experience inmentoring junior analysts and managing risk modelling projects.

·        Familiarity with cloudcomputing platforms (AWS, Azure, GCP) and big data technologies is a plus.