Senior Manager-Data Science-Data Scientist
Gurugram, Haryana, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s listing: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and build application, behavioral and collections credit risk scorecards
Develop machine learning models for collections and delinquency prediction
Extract, clean and preprocess data from various sources using SQL
Monitor, backtest, recalibrate and validate models to regulatory standards
Document modeling processes and results for governance and audit
From the employer’s posting
Design and build credit risk scorecards (application, behavioral, and collections scorecards)
Develop and implement machine learning models for collections performance and delinquency prediction using Python
Extract, clean, and preprocess data from various sources using SQL.
Monitor model performance, conduct backtesting, recalibration, and validation adhering to regulatory standards.
Document modeling processes, assumptions, and results for internal governance and audit purposes.
What you’ll bring
All qualificationsCore experience
- Strong proficiency in Python and SQL
- Proven experience in credit risk scorecard development and collections modeling
- Understanding of credit risk metrics such as delinquency, KS, Gini and AUC
- Experience with machine learning, feature engineering and model monitoring
- Bachelor's in Engineering or Master's in Statistics or Mathematics
Qualification wording
Strong proficiency in Python and SQL for data manipulation, modeling, and automation.
Proven experience in credit risk scorecard development and collections/account management modeling.
Understanding of credit risk model metrics (Delinquency, KS, Gini, AUC, etc.)
Experience with machine learning algorithms, feature engineering, and model monitoring techniques.
Bachelor’s in Engineering or Master’s degree in Statistics, Mathematics
Education & alternatives
Experience with machine learning algorithms, feature engineering, and model monitoring techniques. Bachelor’s in Engineering or Master’s degree in Statistics, Mathematics Familiarity with credit bureau data and experience working in a BFSI environment.
Tools in this posting
- Python
- SQL
- pandas
- scikit-learn
Source — Tool mentions in context
Extract, clean, and preprocess data from various sources using SQL. Develop and implement machine learning models for collections performance and delinquency prediction using Python (including libraries like pandas, scikit-learn). Monitor model performance, conduct backtesting, recalibration, and validation adhering to regulatory standards.
Document modeling processes, assumptions, and results for internal governance and audit purposes. Strong proficiency in Python and SQL for data manipulation, modeling, and automation. Proven experience in credit risk scorecard development and collections/account management modeling.
Design and build credit risk scorecards (application, behavioral, and collections scorecards) to predict creditworthiness and optimize account management strategies. Extract, clean, and preprocess data from various sources using SQL. Develop and implement machine learning models for collections performance and delinquency prediction using Python (including libraries like pandas, scikit-learn).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 12, 2026 · 74 days ago
- Recorded sightings
- 303
- Last seen by us
- Oct 25, 2026
- Employer says posted
- Apr 14, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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- Have your resume and examples of relevant work ready.
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- Ask the employer about the pay range before committing time to the process.
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Job description
Design and build credit risk scorecards (application, behavioral, and collections scorecards) to predict creditworthiness and optimize account management strategies.
Extract, clean, and preprocess data from various sources using SQL.
Develop and implement machine learning models for collections performance and delinquency prediction using Python (including libraries like pandas, scikit-learn).
Monitor model performance, conduct backtesting, recalibration, and validation adhering to regulatory standards.
Collaborate with business and data teams to translate credit risk requirements into modeling specifications.
Document modeling processes, assumptions, and results for internal governance and audit purposes.
Strong proficiency in Python and SQL for data manipulation, modeling, and automation.
Proven experience in credit risk scorecard development and collections/account management modeling.
Understanding of credit risk model metrics (Delinquency, KS, Gini, AUC, etc.)
Experience with machine learning algorithms, feature engineering, and model monitoring techniques.
Bachelor’s in Engineering or Master’s degree in Statistics, Mathematics
Familiarity with credit bureau data and experience working in a BFSI environment.
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Gurugram, Haryana, India
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- Work authorization
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