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Data Analyst with less than a year in SQL, Power BI, and Python for business intelligence.
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Assessing your cultural and operational fit
Data Analyst with hands-on experience turning large, complex datasets (100K+ records) into actionable business insights across e-commerce, fintech, and SaaS domains. Skilled in SQL, Power BI (DAX), Excel, and Python, with experience in KPI development, dashboarding, root cause analysis, and stakeholder-focused reporting.
Malla Reddy Engineering College
Bachelor of Technology · Information Technology
November 21, 2021 – May 30, 2025
K.L.N Junior College
Intermediate (MPC)
June 1, 2019 – May 31, 2021
RavenStack — SaaS Pre-Launch Growth, Churn & Retention Analytics
April 30, 2026 – Present
Built a 5-layer SQL data model (43 views, PostgreSQL) across 30K+ records and 500 accounts, standardizing churn logic after identifying 79% inconsistency in raw churn flags. Analyzed a 24-month SaaS dataset; identified a 3.6x cohort quality decline driven by an acquisition mix shift, with ads contribution dropping from 52% to 12%. Developed a multi-factor churn risk model (usage, support, downgrade signals) flagging 135 high-risk accounts representing $2.68M in MRR exposure. Designed a 7-page Power BI dashboard (42 visuals, DAX) covering retention decay and survival curves; identified a $1.92M MRR preservation opportunity.
View ProjectFlowPay - Payment Risk & Performance Analysis
February 28, 2026 – April 29, 2026
Performed a 7-layer SQL analysis of a payments platform; found payment failures (not fraud) drove ~70% of INR 810M revenue leakage, with only 25% recovered via retries. Built a behavioral risk scoring model (Low/Medium/High tiers) using velocity and retry patterns; identified INR 275M-350M+ in recoverable revenue. Differentiated fraud (identity-driven: account takeover, identity theft) from refunds (operational: wrong amounts, duplicates, merchant errors) to enable targeted fixes. Built standardized SQL definitions for payment funnel metrics (success, failure, retry) to support consistent analytical reporting.
View ProjectE-Commerce Operations & Retention Optimization (Olist)
December 28, 2025 – January 30, 2026
Analyzed 100K+ orders across 9 relational tables (R$15.8M GMV); found 87% of customers never returned after first purchase. Identified seller dispatch delays as the top driver of 10.25% SLA breaches and elevated poor-review rates. Designed 3 stakeholder-mapped Excel dashboards - Executive, Marketing/CX, and Operations/Logistics - translating raw data into decision-ready views; recommended a Seller Tiering System to improve retention and SLA performance. Validated joins across 9 tables using row-count audits; performed data cleaning, null handling, and created derived columns to ensure accurate metric calculation; published methodology and insights as a Medium case study.
View ProjectPower BI Essentials: Data Transformation & Modeling with DAX
Edureka
May 17, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data analysis techniques across diverse business scenarios (SaaS, Fintech, E-commerce). The pursuit of certifications and publications indicates a strong drive for continuous improvement and knowledge sharing, which aligns well with a culture of learning and collaboration. However, the lack of professional experience means cultural fit in a corporate setting is yet to be fully proven.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving skills, and the ability to translate complex data into stakeholder-focused insights. Their project descriptions highlight a structured approach to data analysis and reporting, indicating good operational fit for roles requiring detailed data investigation and clear communication of findings.