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Mid-level, generalist data role in metro with popular 3–5 year band increases applicant competition.
Strong technical skills are transferable, but required lending and credit-risk domain knowledge raises industry specificity.
Mandatory expert SQL, BI, Python/R and Tier-1 institute educational requirement make screening highly selective.
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Lead design, development, and deployment of scalable executive dashboards using Tableau or Power BI, standardizing KPIs and visualizations.
Write, optimize, and audit complex SQL queries and data models on cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) to support advanced analytics.
Conduct deep-dive fintech analytics around loan portfolio, risk metrics, and predictive modeling using Python or R to inform leadership decisions.
3–5 years experience in data analytics/business intelligence, with at least 1 year in Fintech, Banking, NBFC, or Financial Services.
Bachelor's or Master's degree in Engineering, Computer Science, Statistics, Mathematics, or related quantitative field from a Tier-1 institute (IIT, NIT, BITS, or equivalent).
Expert level SQL skills including complex query optimization, window functions, and cloud data warehouses.
Advanced expertise in Tableau or Power BI and proficiency in Python or R for statistical analyses.
Experienced in fintech or retail lending analytics with strong domain knowledge of credit risk and portfolio health metrics.
Skilled at translating complex business problems into analytical models and communicating findings to C-suite/executive leadership.
Capable of architecting and overseeing BI solutions with a focus on governance, performance, and mentoring junior analysts.