
Data Analyst with less than a year in SQL, Power BI, and Python for business intelligence.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
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.