Senior Data Analyst

Job description Senior Data Analyst Credit Risk & Lending Location: Chennai Work Mode: Work From Office Experience: 4+ years Shift Timings: 1:30 PM 10:30 PM IST Job Type: Full Time About the Role: We are looking for a hybrid Senior Data Analyst who thrives at the intersection of advanced data engineering and financial risk analysis. In this role, you won't just run queries—you will own the narrative of our credit card and consumer lending portfolios. You will transform massive, complex datasets into scalable Power BI architectures and Python scripts, translating data into actionable insights on portfolio performance, delinquency trends, and loss forecasting. Key Responsibilities: 1. Portfolio Analysis & Risk Insights Monitor Portfolio Health: Analyze credit card performance across the entire lifecycle: acquisition, activation, utilization, delinquency, payment behavior, and attrition. Risk Metrics & Forecasting: Track and report on critical risk indicators, including delinquency buckets, provisioning trends, and loss forecasts. Behavioral Anomalies: Detect shifts in customer behavior and pinpoint the underlying drivers of risk exposure. Stakeholder Storytelling: Partner with global risk, finance, and tech teams to deliver clear, data-driven insights to senior leadership. 2. Advanced Data Engineering & Analytics Heavy SQL Lifting: Write and optimize complex queries using advanced transformations (window functions, ranking logic, aggregation, and performance tuning). Automation & Modeling: Use Python for data scripting, automation and statistical risk modeling. Data Hygiene: Proactively identify and resolve duplicate records and complex data quality issues. 3. Power BI Architecture & Governance Scalable Modeling: Design, build, and maintain enterprise-level data models (>1GB) using Power BI and Excel. Advanced DAX: Write complex DAX measures and calculated columns optimized for performance. Security & Administration: Implement Row-Level Security (RLS), workspace governance, incremental refreshes, and gateway management. Technical Toolkit Required: Advanced SQL: Deep expertise in Joins, Subqueries, ROW_NUMBER, RANK, LEAD/LAG, Unions, Regex, and Query Optimization. Python: Proficient in scripting, automation, data structures (lists/dictionaries), loops, and robust try/except error handling. Power BI: Mastery of large PBIX files, RLS, incremental refresh, advanced DAX, and Power BI Service administration. Excel: Strong hands-on experience with statistical risk analysis, pivot modeling, and advanced reporting. Qualifications & Soft Skills: Education & Experience: Bachelor’s degree with 5+ years of relevant experience OR a Master’s degree with 4+ years of experience in Data Analytics or Business Intelligence. Domain Expertise: Proven experience in the Financial Services sector, specifically handling lending, credit cards, or consumer credit products. Communication: Exceptional data storytelling skills with the ability to explain complex technical or statistical findings to non-technical business partners. Mindset: Sharp analytical thinking, strong attention to detail, and the ability to work independently in a fast-paced, global environment.