Summary
Overview
Work History
Education
Skills
Timeline
Generic
Sresha Raha

Sresha Raha

Bangalore

Summary

Senior Analyst with over 6 years of experience delivering data-driven solutions across Retail Marketing, FMCG, and Insurance industries. Experienced in product analytics, guest segmentation, churn modeling, loyalty campaign measurement, fraud detection, and building self-serve dashboards to support business teams. Skilled in collaborating cross-functionally to translate business needs into scalable analytics frameworks and actionable insights.

Overview

6
6
years of professional experience

Work History

Senior Data Analyst - Loyalty Analytics

Target
Bangalore
12.2024 - Current
  • Led a post-campaign deep dive using SQL to analyze redemption patterns and offer performance. Identified 100% overstretching of spending thresholds, which diluted guest response. Recommended offer tier reductions, which led to improved guest engagement and turned a 30% underperformance into a 50% outperformance of forecasted promo sales and markdowns.
  • Conducted cross-functional analysis on store-wide campaign performance to understand the drop in redemption, despite high guest engagement. Identified overlapping category offers as a key driver of cannibalization, and poor offer utilization. Recommended limiting concurrent offers, and introducing in-journey nudges to improve offer clarity and redemption accuracy.
  • Analyzed historical campaigns to compare game vs. Offer performance and uncovered audience selection bias—offer audiences had stronger baseline engagement. Designed a testing strategy using audience mirroring, stratified sampling across segments, and matched offer tiers. Introduced cooling periods to ensure fair attribution; currently leading pre-selection testing, and collaborating cross-functionally on rollout plans.

Senior Data Analyst - Products Analytics

Target
Bangalore
08.2023 - 11.2024
  • Redefined bot identification logic by integrating guest profile-level signals, correcting misclassifications and false flagging, which increased the digital identification rate by 3–4%, and improved targeting accuracy across digital channels.
  • Automated the Identity Resolution Rate (IRR) report by streamlining manual processes and redefining profile identification logic to fix exclusion errors in name matching, improving data accuracy, and uplifting the profile resolution rate by 13%.
  • Led Churn Threshold Analysis by segmenting guests based on GLTV behavior and churn probability to identify mid-risk segments with high retention potential, directly influencing re-engagement strategic planning in guest retention campaigns. Built and maintained a GLTV Churn Dashboard in DOMO to monitor guest attrition trends over time, and support data-driven retention efforts.
  • Strengthened data governance and compliance by analyzing profile-store mapping inconsistencies, resolving visitor-to-profile mismatches, and identifying regulatory risks tied to health-related data. Collaborated cross-functionally with Sourcing, Profile, and Engagement teams to detect and remediate data retention gaps, ensuring system-wide legal alignment, and audit readiness.
  • Delivered Weekly Business Report (WBR) analysis focused on traffic and new guest performance, identifying acquisition and retention trends, spotlighting traffic declines, and surfacing re-engagement opportunities for lapsed guests; enabled stakeholders to prioritize initiatives and align strategies with business objectives.

Senior Analyst - Retail Analytics

Evalueserve
Bangalore
09.2021 - 08.2023
  • Analyzed weekly sales, product trends, and market performance for Kraft Heinz across major U.S. retailers (Walmart, Target, Amazon) to drive sales growth, improve profitability, support P&L tracking, and flag low-performing SKUs for promotional or assortment adjustments.
  • Wrote and optimized SQL queries using DBT and Snowflake to analyze sales data, uncover profit patterns, and deliver actionable recommendations that enhanced category visibility and sales efficiency.
  • Built and maintained a Market Share Dashboard in Tableau to monitor daily sales, customer KPIs, product placement, and share performance across Category, Brand, and UPC levels—enabling channel-level insights and cross-retailer comparisons.
  • Investigated seasonal underperformance (e.g., Halloween) through year-over-year analysis, identifying customer shifts toward competing products due to aggressive pricing; recommended assortment and promotional changes to recover market share.
  • Delivered digital shelf analytics and cross-platform benchmarking by evaluating product visibility, descriptions, and placement across major online retailers; identified content quality gaps impacting conversions, and guided listing optimizations to improve digital performance.

Senior Analyst - Fraud Risk Management

MetLife Insurance
Noida
06.2019 - 05.2021
  • Developed and deployed a TPA Management Tool that automated claims administration and drove process efficiency, resulting in a half-yearly cost saving of $240K, and a Provider Comparison Framework to assess provider performance against competitors, aiding successful service price negotiations.
  • Designed and implemented a comprehensive Fraud Analytics Tool using SQL and Power BI that flagged high-risk claims through statistical rule sets and scoring mechanisms, contributing to annual savings of over $500K, and significantly improving fraud detection accuracy.
  • Created fraud scoring logic to accelerate claims decision-making, reduce manual efforts, and enhance turnaround time. Collaborated with claims adjusters and network teams to align analytics with day-to-day workflows, and ensure tool adoption across teams.
  • Applied statistical methodologies, including hypothesis generation and hypothesis testing, to analyze claims data and deliver predictive insights that improved claim accuracy and reduced processing inefficiencies.
  • Built a fully automated Weekly Pharmacy Fraud Detection Tool that reduced fraud detection turnaround time from one month to one week. Streamlined data ingestion from email-based Excel files and integrated dynamic fraud hypothesis checks, enabling timely detection of high-risk pharmacy behaviors.

Education

Master's - Statistics

University of Delhi
01.2019

Bachelor's - Statistics

University of Calcutta
01.2017

Skills

  • Tools and languages: SQL, Python, Hive, Hadoop, R, and GitHub
  • Statistical Techniques: Hypothesis Testing, A/B Testing, Regression, Time Series Forecasting
  • Visualization: Tableau, Power BI, DOMO, Advanced Excel, VBA
  • Specialties: Campaign Analytics, Strategic Analysis, Churn Modeling, Stakeholder Management, Critical Thinking

Timeline

Senior Data Analyst - Loyalty Analytics

Target
12.2024 - Current

Senior Data Analyst - Products Analytics

Target
08.2023 - 11.2024

Senior Analyst - Retail Analytics

Evalueserve
09.2021 - 08.2023

Senior Analyst - Fraud Risk Management

MetLife Insurance
06.2019 - 05.2021

Master's - Statistics

University of Delhi

Bachelor's - Statistics

University of Calcutta

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