Amritanshu
Mumbai
Summary
Data Analyst with 1.5 years + experience at Kotak Mahindra Bank, where I worked with corporate salary account data across 20M+ customers to help teams make faster, smarter decisions. I built dashboards that branch managers on pan india level use daily, cut a reporting process from a full day to 30 minutes, and led a large-scale data migration to AWS. I work mostly in SQL and Python, and I'm comfortable taking a messy business problem and turning it into something actionable.
Overview
1
1
year of professional experience
1
1
Certification
Work History
Data Analyst
Kotak Mahindra Bank Ltd.
Mumbai
12.2024 - Current
- Analyzed bonus credit patterns across 2.5M+ corporate salary accounts to identify the best windows for customer targeting . Directly influenced campaign timing strategy and deposit growth.
- Built and owned a full end-to-end Power BI dashboard (connected to Azure + SQL, refreshing daily) to track customer credit inflows and outflows.The dashboard became the go-to tool for Relationship and Branch Managers to proactively spot at-risk accounts.
- Delivered monthly reports on customer acquisition trends to senior stakeholders, translating data signals into actionable portfolio strategy recommendations.
- Led the migration of 5,000+ lines of SAS/PROC SQL code to MySQL on AWS Redshift, maintaining data integrity throughout a business-critical platform transition and improving query performance in the process
Education
B.Tech - Electronics And Communications Engineering
Birla Institute of Technology
Mesra06-2023
Skills
- BI & Reporting: Power BI, MS Excel, Tableau, Stakeholder Reporting
- Languages & Querying: Advanced SQL, Python (Pandas, NumPy)
- Machine learning (Intermediate Level)
- Cloud & Data Ops: Microsoft Azure, Apache Airflow, AWS (Redshift, S3), SAS
Projects
Deposit Book Growth Dashboard
- Built a automated daily-refresh Power BI dashboard that flagged customers with overnight large credit inflows like (salary, bonus, or lump-sum) as high-potential FD/RD conversion targets.
- Gave Branch Managers a prioritized call list every morning, directly supporting the bank's liability growth strategy by connecting data signals to frontline sales actions.
Customer Churn Prediction
- Framed churn as a business problem first: identified that missing high-risk customers was costlier than false positives, then built an XG-Boost model optimized for recall (80%) — correctly flagging 530 of 670 actual churners on a 10,000 record dataset.
Certification
- Google Advanced Data Analytics Professional Certificate
- Python for Data Science and Machine Learning
- Google AI Essentials Bootcamp
Timeline
Data Analyst
Kotak Mahindra Bank Ltd.
12.2024 - Current
B.Tech - Electronics And Communications Engineering
Birla Institute of Technology