Credit Risk Modeling, Analytics & ML Opportunities | 2–5 Years Experience

Risk Inn

full-time

Required skills

Python
banking
cross-functional
data science
decision trees
predictive models
regression
SAS
SQL

About the role

Risk Inn

Website: riskinn.com
Job details:

𝐇𝐢𝐫𝐢𝐧𝐠 𝐌𝐚𝐧𝐝𝐚𝐭𝐞 | Credit Risk ML, IFRS 9 / ECL & Scorecard Modeling Roles | 2–5 Years Experience

👨‍💼 Openings Across: 3 Role Categories

📍 Location: Bangalore, India / Remote & Hybrid, depending on role and project requirements

🆔 Job ID: CR-SIM

💰 Salary Range: ₹18-30 LPA, subject to experience, role fit, and interview performance

💡𝐀𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞:

At Risk Inn, we specialize in connecting leading banks, investment institutions, consulting firms, and financial services clients with high-quality talent across risk management, quantitative finance, financial markets, and analytics. Through our curated professional communities and practitioner-driven ecosystem, we bring relevant career opportunities to finance and risk professionals globally. Our goal is to bridge the gap between skilled professionals and roles that meaningfully contribute to both individual career growth and organizational impact.

We are supporting our client, a leading global risk analytics and advisory firm, in hiring professionals across machine learning-based credit risk analytics, IFRS 9 / ECL modeling, scorecard modeling, portfolio modeling, and credit risk data science workflows.

These roles are suitable for candidates with 2–5 years of experience across machine learning, credit risk modeling, IFRS 9 / ECL analytics, scorecard development, portfolio analytics, and predictive risk modeling. Working knowledge of Python, Excel, SAS, SQL, and statistical modeling techniques will be useful depending on the specific role and project requirements.

Think you're the right fit? Keep reading!

𝐑𝐨𝐥𝐞 1: 𝐈𝐅𝐑𝐒 𝟗 / 𝐄𝐂𝐋 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠

𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬

✅ Support IFRS 9 Expected Credit Loss modeling across credit portfolios

✅ Analyze PD, LGD, EAD, staging, default, delinquency, and portfolio movement data

✅ Assist in developing and maintaining lifetime PD, LGD, EAD, and ECL calculation frameworks

✅ Support staging assessment, significant increase in credit risk analysis, and macroeconomic scenario application

✅ Perform data extraction, validation, reconciliation, and analysis for impairment and ECL reporting workflows

✅ Prepare analytical outputs for IFRS 9 reporting, portfolio monitoring, management review, and governance forums

✅ Support model monitoring, back-testing, sensitivity analysis, overlays, and documentation of assumptions

✅ Collaborate with credit risk, finance, model risk, reporting, data, audit, and technology teams

🛠️ 𝐂𝐨𝐫𝐞 𝐒𝐤𝐢𝐥𝐥𝐬

2–5 years of experience in IFRS 9, ECL modeling, credit risk modeling, impairment analytics, or related banking functions
Strong understanding of PD, LGD, EAD, default definitions, staging, lifetime ECL, and macroeconomic scenarios
Experience working with credit risk data, portfolio performance data, impairment models, and reporting outputs
Ability to perform data validation, reconciliations, model checks, variance analysis, and assumption reviews
Good understanding of IFRS 9 reporting requirements, credit risk metrics, and governance expectations
Working knowledge of Excel, Python, SAS, or SQL
Strong documentation mindset with attention to auditability, controls, and process clarity
Ability to work with stakeholders across risk, finance, reporting, model validation, audit, and technology

𝐑𝐨𝐥𝐞 2: 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐮𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧 (𝐂𝐫𝐞𝐝𝐢𝐭 𝐑𝐢𝐬𝐤)

𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬

✅ Develop and support machine learning models for credit risk analytics, scoring, segmentation, and portfolio monitoring

✅ Build predictive models for default risk, delinquency risk, collections prioritization, early warning signals, and customer segmentation

✅ Perform feature engineering, data preprocessing, model training, testing, validation, and performance comparison

✅ Support challenger model development using techniques such as logistic regression, decision trees, random forest, XGBoost, and similar models

✅ Evaluate model performance using metrics such as ROC-AUC, KS, Gini, precision, recall, stability, and population drift

✅ Prepare model documentation, explainability outputs, monitoring reports, and business interpretation notes

✅ Collaborate with credit risk, analytics, data science, business, model validation, and technology teams

🛠️ 𝐂𝐨𝐫𝐞 𝐒𝐤𝐢𝐥𝐥𝐬

2–5 years of experience in credit risk analytics, machine learning, data science, predictive modeling, or banking analytics
Hands-on experience using Python for data analysis, feature engineering, model development, and model evaluation
Working knowledge of machine learning models such as logistic regression, decision trees, random forest and XGBoost
Ability to validate model outputs, explain drivers, identify data issues, and convert model results into business-ready insights
Good understanding of model performance metrics, model monitoring, explainability, and governance requirements

𝐑𝐨𝐥𝐞 𝟑: 𝐒𝐜𝐨𝐫𝐞𝐜𝐚𝐫𝐝 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠

𝐊𝐞𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬

✅ Develop, validate, and monitor credit risk scorecards across retail, SME, and portfolio-level lending products

✅ Support application scorecard, behavioural scorecard, collection scorecard, and PD scorecard development

✅ Analyze borrower, bureau, transaction, delinquency, and portfolio data to identify risk drivers

✅ Perform variable selection, binning, weight-of-evidence analysis, information value testing, and model performance checks

✅ Build and maintain scorecard models using logistic regression and related statistical techniques

✅ Prepare model documentation, monitoring reports, validation outputs, and business interpretation notes

✅ Collaborate with credit risk, analytics, business, policy, collections, and technology teams

🛠️ 𝐂𝐨𝐫𝐞 𝐒𝐤𝐢𝐥𝐥𝐬

2–5 years of experience in credit risk scorecard development, credit risk analytics, banking analytics, or related functions
Strong understanding of credit scorecards, PD models, delinquency behaviour, bureau data, and portfolio risk metrics
Hands-on experience with logistic regression, WOE, IV, KS, Gini, ROC-AUC, model calibration, and validation checks
Ability to analyze borrower-level and portfolio-level credit data and convert findings into decision-ready insights
Good understanding of credit policy, risk segmentation, approval strategies, and scorecard monitoring
Working knowledge of Excel, Python, SAS, or SQL
Strong analytical thinking, documentation skills, and attention to detail
Ability to work with cross-functional teams across risk, business, analytics, policy, and technology

🎁 𝐖𝐡𝐚𝐭 𝐘𝐨𝐮 𝐆𝐚𝐢𝐧:

✅ Opportunity to work with a leading global risk analytics and advisory firm

✅ Exposure to machine learning workflows, IFRS 9 / ECL analytics, scorecard modeling, credit risk modeling, and portfolio analytics

✅ Hybrid and remote role opportunities

✅ Strong learning curve across predictive modeling, portfolio analytics, risk frameworks, and model governance

✅ Opportunity to work on high-impact credit risk analytics and modeling initiatives

✅ Exposure to stakeholders across risk, analytics, finance, reporting, audit, and technology teams

✅ Collaborative environment with strong professional growth opportunities

⏰ Ready to take the next step? Timing is key!

📩 Send your resume to empowering@riskinn.com

Subject Line: Application for Job ID CR-SIM

Along with your resume, please also include 2–3 lines answering the screening questions below in the same email:

𝐒𝐜𝐫𝐞𝐞𝐧𝐢𝐧𝐠 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬

Job ID: CR-SIM

Which role are you most aligned with: Scorecard Modeling Analyst, IFRS 9 / ECL Modeling Analyst, or Credit Risk ML / Python Modeling Analyst? Briefly explain your relevant experience.
What types of credit risk models, portfolio datasets, scorecards, IFRS 9 / ECL frameworks, or machine learning workflows have you worked on in your current or previous roles?
Which tools, programming languages, or modeling techniques have you used for credit risk analytics and model development: Excel, SQL, SAS, Python, logistic regression, scorecards, IFRS 9 models, or machine learning models?

OR reach out via DM / WhatsApp +91-885-970-2673 with Job ID CR-SIM

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