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 Analytics Product & Innovation team. This is a hands-on analytics role focused on developing and enhancing data-driven products using consumer bureau data, statistical techniques and machine learning. You will work from use-case exploration and analytical prototyping through validation, UAT and productisation support. The role is suited to someone who enjoys working directly with data and code, can build robust analytical solutions, and wants to see those solutions become repeatable products used by clients. Strong analytics and coding capability are more important than prior experience in any one risk domain.
What you'll do
- Analyse large and complex bureau and financial-services datasets to identify patterns, signals and opportunities for new or enhanced analytics products.
- Translate a product idea or industry use case into a structured analytical approach, prototype and measurable success criteria.
- Build and benchmark statistical and machine-learning models, scores, segmentations, features and decision-support components appropriate to the use case.
- Perform data preparation, exploratory analysis, feature engineering, variable selection and analytical dataset creation using efficient Python and SQL code.
- Apply robust validation to assess predictive performance, stability, interpretability and business suitability; document assumptions and limitations clearly.
- Create reusable analytical code, utilities and automated workflows that can support repeatable product development rather than one-off analysis.
- Partner with Product and Technology teams on analytical requirements, UAT, defect investigation and productisation of new or enhanced capabilities.
- Support performance reviews of existing analytics products and identify opportunities for efficiency, feature enhancement or methodology improvement.
- Prepare clear analytical documentation and explain methodologies, results and product value to internal stakeholders and, where required, clients.
- Follow applicable data-security, model-governance, documentation and compliance standards.
What success looks like
- High-quality, analytical prototypes and product enhancements that meet agreed acceptance criteria.
- Demonstrable improvement in product performance, usability or analytical coverage where an enhancement is made.
- Reusable, well-documented code and analytical assets that reduce repeated effort and support scale.
- Effective UAT support, low analytical defect leakage and strong documentation / governance discipline.
What you'll need to bring
- Approximately 3+ years of experience in analytics, data science, decision science, statistical modelling or a closely related field.
- Strong hands-on proficiency in Python for data manipulation, exploratory analysis, statistical modelling and machine learning.
- Strong working knowledge of SQL, including the ability to extract, transform and analyse large and complex datasets.
- Sound grounding in applied statistics, including sampling, distributions, hypothesis testing, regression and model evaluation.
- Hands-on experience with common supervised and unsupervised techniques such as regression, tree-based methods, ensemble methods, gradient boosting, classification, clustering and segmentation.
- Understanding of model-development practices including train/validation/test design, cross-validation, overfitting, performance metrics, stability and interpretability.
- Strong data-wrangling, data-quality assessment, feature-engineering and analytical validation skills.
- Ability to convert a business question into a structured analytical approach and communicate findings clearly to technical and non-technical stakeholders.
- A disciplined approach to coding, documentation, reproducibility and quality assurance.
Good to have
- SAS or another statistical programming environment.
- Git or similar version-control tools and collaborative coding practices such as peer review.
- Cloud analytics platforms, distributed computing or tools such as Spark / Databricks.
- Experience automating analytical workflows or developing reusable analytics libraries and utilities.
- Exposure to productionisation, model monitoring or model-governance frameworks.
- Exposure to consumer lending, credit risk, bureau data, fraud, portfolio or decision analytics.
- Experience taking an analytical prototype through UAT, implementation or productisation.
- Experience in analytics product development or working closely with product and technology teams.
Domain note: Experience in credit risk or bureau analytics is valuable, but strong analytics, coding, statistical reasoning are the primary selection criteria.
Additional InformationOur uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why. Experian is also proud to be an Equal Opportunity and Affirmative Action employer. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.
Benefits:
- 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
Recruitment Fraud Awareness - Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address.
Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process. To apply for roles or verify opportunities, please visit experian.com/careers.
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Skills Required
- Approximately 3+ years of experience in analytics, data science, decision science, statistical modeling, or a closely related field.
- Strong hands-on proficiency in Python for data manipulation, exploratory analysis, statistical modeling, and machine learning.
- Strong working knowledge of SQL for extracting, transforming, and analyzing large and complex datasets.
- Applied statistics knowledge, including sampling, distributions, hypothesis testing, regression, and model evaluation.
- Hands-on experience with supervised and unsupervised techniques, including regression, tree-based methods, ensemble methods, gradient boosting, classification, clustering, and segmentation.
- Understanding of model-development practices, including train/validation/test design, cross-validation, overfitting, performance metrics, stability, and interpretability.
- Strong data wrangling, data-quality assessment, feature-engineering, and analytical validation skills.
- Ability to translate business questions into structured analytical approaches and communicate findings to technical and non-technical stakeholders.
- Disciplined approach to coding, documentation, reproducibility, and quality assurance.
- Experience with SAS or another statistical programming environment.
- Experience with Git or similar version-control tools and collaborative coding practices such as peer review.
- Experience with cloud analytics platforms, distributed computing, Spark, or Databricks.
- Experience automating analytical workflows or developing reusable analytics libraries and utilities.
- Exposure to productionisation, model monitoring, or model-governance frameworks.
- Exposure to consumer lending, credit risk, bureau data, fraud, portfolio, or decision analytics.
- Experience taking analytical prototypes through UAT, implementation, or productisation.
- Experience in analytics product development or collaboration with product and technology teams.
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.
Experian Insights
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.
