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Risk Analyst – Data Science & Analytics
Mumbai, Maharashtra, India
Likely evergreen, first seen by us 2 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingAnalyze MSME commercial bureau and portfolio data for lending insights
Develop and validate bureau-based credit risk scorecards and predictive models
Engineer features from bureau and tradeline data and build analytical datasets
Translate lending challenges into structured analytical solutions
Deliver proofs of concept and support client and pre-sales technical discussions
From the employer’s posting
Analyze MSME commercial bureau and portfolio data to generate actionable insights
Develop, validate, and optimize bureau-based credit risk scorecards and predictive models
Engineer robust features from bureau and tradeline data, conduct data quality assessments
Translate lending and business challenges into structured analytical solutions
deliver proofs of concept, demonstrate the value of analytics solutions, support technical discussions
What you’ll bring
All qualificationsCore experience
- 3+ years of experience in Data Science, Credit Risk Analytics, Decision Science, or Statistical Modelling, with hands-on exposure to lending analytics.
- Experience in MSME/SME lending and commercial bureau analytics is essential.
- Strong proficiency in Python and SQL, with experience building scalable analytical solutions, performing feature engineering, and working with large, complex credit-risk datasets.
- Hands-on experience developing and validating credit risk scorecards, predictive models, and segmentation frameworks using statistical and machine learning techniques, with a practical understanding of model interpretability and business applicability.
- Strong knowledge of credit risk modelling methodologies, including WoE, IV, variable selection, model validation, calibration, class imbalance, portfolio segmentation, delinquency analysis, early-warning indicators, and performance monitoring.
- Deep understanding of commercial bureau data and lending portfolios, with the ability to derive meaningful risk insights, assess model performance using metrics such as KS, Gini/AUC, Lift, PSI, and translate findings into actionable business recommendations.
Qualification wording
3+ years of experience in Data Science, Credit Risk Analytics, Decision Science, or Statistical Modelling, with hands-on exposure to lending analytics. Experience in MSME/SME lending and commercial bureau analytics is essential.
Strong proficiency in Python and SQL, with experience building scalable analytical solutions, performing feature engineering, and working with large, complex credit-risk datasets.
Hands-on experience developing and validating credit risk scorecards, predictive models, and segmentation frameworks using statistical and machine learning techniques, with a practical understanding of model interpretability and business applicability.
Strong knowledge of credit risk modelling methodologies, including WoE, IV, variable selection, model validation, calibration, class imbalance, portfolio segmentation, delinquency analysis, early-warning indicators, and performance monitoring.
Deep understanding of commercial bureau data and lending portfolios, with the ability to derive meaningful risk insights, assess model performance using metrics such as KS, Gini/AUC, Lift, PSI, and translate findings into actionable business recommendations.
Posting record
Report an errorLikely evergreenReposted 3 times since Sep 30, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.
- Status in our records
- Live
- First seen by us
- Nov 2, 20262 days ago
- Recorded sightings
- 3
- Last seen by us
- Nov 4, 2026
- Reposted
- 3 times since Sep 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
Experian is hiring
25 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Scientist hiring is picking up
- Takes jobs down quickly
- 32% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SAS
- SQL
- Databricks
- Spark
Where the posting names them
Job Description We are looking for a Risk Analyst – Data Science & Analytics to join our Commercial Bureau Analytics & Pre-Sales Consulting team. In this hands-on role, you'll leverage commercial bureau data, statistical modelling, and machine learning to solve credit risk challenges for banks, NBFCs, fintechs, and MSME lenders. You'll develop bureau-based risk models, scorecards, segmentation and portfolio analytics solutions, while supporting client-focused analytics and pre-sales initiatives. Strong Python, SQL, credit risk modelling, and MSME/commercial lending expertise are key to success in this role. What you'll do
- Develop, validate, and optimize bureau-based credit risk scorecards and predictive models using statistical and machine learning techniques, ensuring strong performance, stability, and business impact. - Engineer robust features from bureau and tradeline data, conduct data quality assessments, perform portfolio analytics, and build scalable analytical datasets using Python and SQL. - Collaborate closely with clients, pre-sales, Product, and Technology teams to deliver proofs of concept, demonstrate the value of analytics solutions, support technical discussions, and drive successful productisation.
- 3+ years of experience in Data Science, Credit Risk Analytics, Decision Science, or Statistical Modelling, with hands-on exposure to lending analytics. Experience in MSME/SME lending and commercial bureau analytics is essential. - Strong proficiency in Python and SQL, with experience building scalable analytical solutions, performing feature engineering, and working with large, complex credit-risk datasets. - Hands-on experience developing and validating credit risk scorecards, predictive models, and segmentation frameworks using statistical and machine learning techniques, with a practical understanding of model interpretability and business applicability.
- Deep understanding of commercial bureau data and lending portfolios, with the ability to derive meaningful risk insights, assess model performance using metrics such as KS, Gini/AUC, Lift, PSI, and translate findings into actionable business recommendations. - Excellent stakeholder management and communication skills, with the ability to collaborate across business, product, technology, and client teams. Experience with tools and practices such as Git, SAS, Spark, Databricks, model governance, productionisation, consulting, pre-sales, or client-facing analytics engagements is highly valued. Additional Information
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Has Experian posted this job before?
Yes. We’ve followed 5 other Risk Analyst – Data Science & Analytics jobs there since September 2026. 3 came down, usually after about 9 days. 2 are still up.
If this one keeps the same pace, it may come down around November 11.
Large employers often post one title for several teams, so these can be separate openings.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
Job Description
We are looking for a Risk Analyst – Data Science & Analytics to join our Commercial Bureau Analytics & Pre-Sales Consulting team. In this hands-on role, you'll leverage commercial bureau data, statistical modelling, and machine learning to solve credit risk challenges for banks, NBFCs, fintechs, and MSME lenders. You'll develop bureau-based risk models, scorecards, segmentation and portfolio analytics solutions, while supporting client-focused analytics and pre-sales initiatives. Strong Python, SQL, credit risk modelling, and MSME/commercial lending expertise are key to success in this role.
What you'll do
- Analyze MSME commercial bureau and portfolio data to generate actionable insights across acquisition, underwriting, risk segmentation, portfolio monitoring, early warning, and collections strategies.
- Translate lending and business challenges into structured analytical solutions, defining data requirements, success metrics, risk segments, and modelling approaches aligned to client needs.
- Develop, validate, and optimize bureau-based credit risk scorecards and predictive models using statistical and machine learning techniques, ensuring strong performance, stability, and business impact.
- Engineer robust features from bureau and tradeline data, conduct data quality assessments, perform portfolio analytics, and build scalable analytical datasets using Python and SQL.
- Collaborate closely with clients, pre-sales, Product, and Technology teams to deliver proofs of concept, demonstrate the value of analytics solutions, support technical discussions, and drive successful productisation.
- Create reusable analytics frameworks, features, and modelling assets while maintaining high standards of validation, governance, documentation, compliance, and data security.
Qualifications
What you'll need to bring
- 3+ years of experience in Data Science, Credit Risk Analytics, Decision Science, or Statistical Modelling, with hands-on exposure to lending analytics. Experience in MSME/SME lending and commercial bureau analytics is essential.
- Strong proficiency in Python and SQL, with experience building scalable analytical solutions, performing feature engineering, and working with large, complex credit-risk datasets.
- Hands-on experience developing and validating credit risk scorecards, predictive models, and segmentation frameworks using statistical and machine learning techniques, with a practical understanding of model interpretability and business applicability.
- Strong knowledge of credit risk modelling methodologies, including WoE, IV, variable selection, model validation, calibration, class imbalance, portfolio segmentation, delinquency analysis, early-warning indicators, and performance monitoring.
- Deep understanding of commercial bureau data and lending portfolios, with the ability to derive meaningful risk insights, assess model performance using metrics such as KS, Gini/AUC, Lift, PSI, and translate findings into actionable business recommendations.
- Excellent stakeholder management and communication skills, with the ability to collaborate across business, product, technology, and client teams. Experience with tools and practices such as Git, SAS, Spark, Databricks, model governance, productionisation, consulting, pre-sales, or client-facing analytics engagements is highly valued.
Additional Information
- Great compensation package and discretionary bonus plan
- Core benefits include pension, health Insurance and term life Insurance, Sharesave scheme and more!
- 25 days annual leave with 13 bank holidays and 3 volunteering days. You can also purchase additional annual leave.
- You will report to Senior Analytics Consultant.
- Role Location: Mumbai
- Experian is an equal opportunities employer
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Company Description
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.
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- Pay
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- Location & working pattern
Mumbai, Maharashtra, India
Working pattern and location restrictions need checking in the full posting.
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