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.
Job DescriptionWe 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.
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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Skills Required
- 3+ years of experience in data science, credit risk analytics, decision science, or statistical modelling, with hands-on lending analytics experience
- Experience in MSME or SME lending and commercial bureau analytics
- Strong proficiency in Python and SQL
- Experience building scalable analytical solutions, feature engineering, and working with large, complex credit-risk datasets
- Hands-on experience developing and validating credit risk scorecards, predictive models, and segmentation frameworks
- Knowledge of WoE, IV, variable selection, model validation, calibration, class imbalance, portfolio segmentation, delinquency analysis, early-warning indicators, and performance monitoring
- Understanding of commercial bureau data and lending portfolios
- Ability to assess model performance using KS, Gini/AUC, Lift, and PSI
- Excellent stakeholder management and communication skills
- Experience with Git, SAS, Spark, Databricks, model governance, productionisation, consulting, pre-sales, or client-facing analytics engagements
Experian Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Experian and has not been reviewed or approved by Experian.
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Healthcare Strength — Medical and dental coverage is described as strong, with expanded mental health resources and telemedicine options. Coverage includes inclusive services such as gender transition and fertility support.
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Leave & Time Off Breadth — Time-off offerings are generous, including substantial PTO/vacation, paid holidays, and paid volunteer days with options to purchase additional leave. Parental leave is available for birth and non-birth parents alongside flexible working arrangements that support work-life balance.
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Retirement Support — Retirement programs include a 401(k) with company matching and contributory pension schemes in some regions. These elements complement base pay and bonuses to form a competitive total rewards package.
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What We Do
Experian unlocks the power of data to create opportunities for consumers, businesses and society. During life’s big moments – from buying a home or car, to sending a child to college, to growing a business exponentially by connecting it with new customers – we empower consumers and our clients to manage data with confidence so they can maximize every opportunity. We gather, analyse and process data in ways others can’t. We help individuals take financial control and access financial services, businesses make smarter decision and thrive, lenders lend more responsibly, and organizations prevent identity fraud and crime. For more than 125 years, we’ve helped consumers and clients prosper, and economies and communities flourish – and we’re not done. Our 20,600 people in 43 countries believe the possibilities for you, and our world, are growing. We’re investing in new technologies, talented people and innovation so we can help create a better tomorrow. About Experian: Bringing data to life requires creativity, passion, flexibility and expertise. We want you to share in our success. That's why we offer rewards that recognise great performance. Working in a culture of collaboration, achievement and respect we will give you the support and encouragement you need to develop your skills and talents and progress your career. Everyday our people bring enthusiasm, innovation and inspiration to work and if this sounds like you connect with us at Experian.
