Job Description

Role Summary:

We are looking for a Risk Analyst - Data Science Analytics to join our Analytics Product Innovation team. In this hands-on role, youll leverage bureau data, statistics, and machine learning to develop and enhance data-driven products. Youll work across the analytics lifecycle, from use-case exploration and prototyping to validation, UAT, and productization. Were looking for a strong coder and analytical thinker who enjoys solving complex problems with data and building scalable solutions that deliver client impact.

What youll be doing:

- Analyze large and complex datasets to uncover insights, identify opportunities, and support the development of cutting-edge analytics products.
- Transform business challenges and product ideas into data-driven solutions through exploratory analysis, feature engineering, statistical modelling, and machine learning.
- Develop, validate, and benchmark predictive models, scores, segmentations, and decision-support solutions, ensuring strong performance, stability, interpretability, and business impact.
- Build scalable and reusable analytical assets using Python and SQL, including automated workflows, utilities, and frameworks that enable repeatable product development.
- Collaborate with Product, Technology, and business teams to define requirements, support UAT, investigate issues, and drive the successful delivery and enhancement of analytics products.
- Communicate analytical insights and methodologies clearly through robust documentation while maintaining high standards for data security, model governance, compliance, and quality assurance. Qualifications

What were looking for:

- 3+ years of experience in Data Science, Analytics,



Decision Science, Statistical Modelling, or a related quantitative field, applying data-driven approaches to solve complex business problems.
- Strong hands-on expertise in Python and SQL, with experience working on large datasets for data preparation, feature engineering, exploratory analysis, modelling, and insight generation.
- Solid foundation in statistics, machine learning, and model development, including regression, classification, clustering, ensemble methods, model validation, performance evaluation, and interpretability.
- Proven ability to transform business questions into structured analytical solutions, communicate insights effectively, and influence decisions across technical and non-technical stakeholders.
- Strong focus on data quality, analytical rigor, reproducible coding, documentation, testing, and best practices throughout the analytics lifecycle.
- Experience with modern analytics ecosystems such as Git, SAS, Spark, Databricks, cloud platforms, workflow automation, model monitoring, governance, and productisation. Exposure to lending, credit risk, bureau, fraud, portfolio, or decision analytics is beneficial but not required.

Domain Note: We welcome candidates from diverse analytics backgrounds. While experience in credit risk or bureau analytics is valued, we primarily seek professionals with strong analytical thinking, coding expertise, statistical reasoning, and a passion for building impactful, data-driven solutions.

This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Risk Analyst - Data Science & Analytics (Mumbai)
🏢 Experian
📍 Mumbai