Data Science with 1+ years in SQL, Tableau & Python
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Assessing your cultural and operational fit
Data/BI analyst with 1.5 years of experience turning product and operational data into clear, decision-ready insights. Strong with SQL, Tableau, and Python, with a focus on uncovering patterns and translating complex data into evidence-based recommendations for business stakeholders. Drawn to customer and marketing analytics, with a methodical, data-first approach that bridges technical and business audiences.
Chandigarh College of Engineering & Technology, Panjab University
B.Tech · Computer Science
August 1, 2021 – June 30, 2025
Quark Software Inc.
Software Engineer – QA
July 1, 2025 – Present
India
Quark Software Inc.
Quality Analyst Intern
January 1, 2025 – June 30, 2025
India
Hotel Booking Segmentation & Cancellation Risk Analysis
June 24, 2026 – Present
Segmented 119K hotel bookings to identify cancellation drivers; found that Groups customers with long lead times cancel at materially higher rates, while Online Travel Agency bookings carry the largest absolute exposure due to volume rather than rate. Surfaced a data quality finding: 99% cancellation rate on Non-Refund bookings was almost entirely concentrated in Groups/Offline TA, indicating the dataset likely conflates B2B block-release with individual cancellations - flagged for stakeholder review before any modeling. Built an interactive Tableau dashboard backed by SQL (CTES, window functions), delivered with a PM decision memo recommending changes to deposit policy, channel mix, and lead-time gating.
E-Commerce Landing Page A/B Test
June 24, 2026 – Present
Analyzed a 21-day experiment across 290K users; detected and excluded users who were misrouted between control and treatment before running primary inference. Reported a null result with full statistical context (two-proportion z-test, confidence interval included zero); time-segmented analysis showed the effect was not stable across the test window. Delivered a PM decision memo recommending no-ship and a re-test design with cleaner group assignment and clear success/guardrail metrics.
Zomato vs. Swiggy: Quick-Commerce Unit Economics Teardown
June 24, 2026 – Present
Compiled and analyzed 8 quarters (FY25-FY26) of financial and operational data for India's two listed food-delivery operators by aggregating investor decks, NSE/BSE filings, and brokerage notes into a clean quarterly dataset. Tracked how Instamart's and Blinkit's quick-commerce margins moved across the period, and flagged Q1 FY26 as the quarter where reported segment performance shifted most. Built a custom HTML/SVG dashboard using an annotation-led visualization style where chart titles state the conclusion, making findings legible to non-analyst stakeholders.
Cultural Fit Analysis
The candidate's academic projects are highly relevant to a Data Science role, showcasing a strong interest and foundational skills in data analysis, statistics, and visualization. However, their professional experience is entirely in Quality Assurance, which, while demonstrating analytical rigor, is not directly aligned with a Data Science career path. This creates a gap in practical, industry-specific data science experience. The diversity of academic projects (hotel bookings, e-commerce, quick-commerce unit economics) indicates a broad curiosity and ability to apply data science techniques across different domains.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills, attention to detail (e.g., identifying data quality issues, misrouted users in A/B tests), and an ability to communicate technical findings to non-technical stakeholders. Their QA experience suggests a methodical approach to identifying issues and improving processes, which is valuable in data analysis for ensuring data integrity and reliable insights. The project descriptions indicate a proactive approach to surfacing insights and making recommendations.