Requirements

2+ years analytics experience, Proficiency in SQL, Degree in quantitative field, Knowledge of Python or R, Data visualization experience

Skills

SQLPythonTableau

Utilize behavioral and transactional data to map customer journeys and identify application drop-off points
Generate insights to inform product development, feature prioritization, and UX improvements
Perform deep-dive analysis on customer churn, loyalty, and lifetime value
Analyze telesales performance data to identify bottlenecks and efficiency gaps
Develop predictive models such as Lead Scoring and Propensity-to-Buy to optimize lead distribution
Design and execute A/B tests and multivariate tests to optimize marketing funnel conversion rates
Develop and maintain attribution models to measure marketing initiative impact
Create and automate KPI dashboards for leadership reporting
Present complex analytical findings to non-technical stakeholders

Minimum 2+ years of experience in a dedicated Analytics role
Experience in Fintech, Banking, E-commerce, or NBFC sectors preferred
Strong proficiency in SQL for data extraction and manipulation
Bachelor's or Master's degree in a quantitative field (Statistics, Economics, Engineering, or Computer Science)
Working knowledge of Python or R
Experience with data visualization tools like Metabase, Tableau, Power BI, or Google Data Studio
Deep understanding of statistical concepts, hypothesis testing, and cohort analysis
Experience with Credit or Personal Loan product analytics is a significant advantage