Risk Analyst Data Science & Analytics

Company Description

• Analyse large bureau and client datasets to identify market trends, portfolio patterns, customer segments, emerging risks and growth opportunities.
• Deliver custom analytics assignments by converting client questions into structured hypotheses, analytical methods, outputs and recommendations.
• Build statistical models, segmentations, benchmarks and diagnostic analyses where they materially improve the quality of insight or decision making.
• Perform data preparation, exploratory analysis, feature engineering and quality checks using efficient Python and SQL code.
• Develop repeatable analytical datasets, code libraries and automated workflows to improve the speed and consistency of recurring market-insight outputs.
• Create clear, decision-oriented charts, tables and narratives that communicate analytical findings without overstating what the data supports.
• Contribute analytical content to industry insight reports, client presentations and other thought-leadership outputs.
• Work with stakeholders to refine requirements, validate findings and ensure the final output addresses the intended business question.
• Maintain best practices for analytical accuracy, documentation, reproducibility and peer review.
• Follow applicable data-security, governance and compliance requirements.

• Accurate, insightful and custom analytics and market-insight deliverables.
• Outputs that translate data into clear business implications and are useful to clients and internal stakeholders.
• Increasing automation and reuse across recurring reports, benchmarks and analytical workflows.
• Strong analytical quality and low rework through disciplined validation and documentation.

Qualifications

• 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.
• 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.

• 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 customer analytics, portfolio analytics, market intelligence, risk analytics, segmentation or benchmarking.
• Experience developing analytical visualisations, dashboards or publication-quality charts using Python or BI tools.
• Experience in banking, lending, fintech, payments, insurance, credit-bureau data or other data-rich industries.
• Experience presenting analytical findings or supporting client-facing deliverables.

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