Headline

Senior Data Analyst | 3.5 yrs in e-commerce & retail sector with focus on data analytics | Future Lead Data Analyst

About

Senior data analyst with 3.5 years track record in the e-commerce, retail and technology industry. Adept at solving complex analytics challenges across demand, supply, discounting and A/B testing. Seeking a senior analytics role to implement data-driven strategies to drive profitability. 1. Delivered $33M in incremental GMV in six months and increased affordable meal order share by 4.37% by scaling a supply-building initiative from a seven city A/B test to forty cities through restaurant recommendation lead-lists, cohort targeting, and automated data pipelines using Redash, SQL & Python 2. Achieved 2x higher ordering conversion in three months by building affordable meal recommendation systems that identified repricing and sampler-variant opportunities for restaurants using sales velocity analysis, ROI scoring that also led to 3.6x higher impressions by using Redash, SQL and Python 3. Delivered 92% P&L projection accuracy for festival season across 20 occasions by building multi-view festival demand analytics and predictive forecasting models using occasion clustering, cuisine composition analysis, cohort behaviour leveraging analytical tools like Google Looker, Python and SQL. Specialities : data analysis, data analytics, Excel, Python, SQL, Redash, Power BI, Big Query, e-commerce, Quick Commerce, retail, demand analytics, supply chain analytics, revenue optimization, A/B testing, business intelligence, business forecasting, data insights. Looking for an amazing lead data analyst ? Contact me at rakshitonwork@gmail.com | +91 9728399933.

Location

Gurugram

AI stack

claude code

gemini

ollama

openai

githubcopilot

ChatGPT

Work experience

Senior Data Analyst at Zomato, Feb 2025 - Present · 1 yr 7 mos, Gurugram, Affordable supply chain analytics 1. Delivered $33M in incremental GMV in six months and increased affordable meal order share by 4.37% by scaling a supply-building initiative from a seven city A/B test to forty cities through restaurant recommendation lead-lists, cohort targeting, and automated data pipelines using Redash, SQL & Python 2. Achieved 2x higher ordering conversion in three months by building affordable meal recommendation systems that identified repricing and sampler-variant opportunities for restaurants using sales velocity analysis, ROI scoring that also led to 3.6x higher impressions by using Redash, SQL and Python 3. Reduced manual reporting effort by 60% in two months by building real-time self-serve dashboards, automated alerting systems, and monitoring pipelines tracking city, cuisine, retention, and contribution-margin metrics using Apache Superset, Docker, Airflow DAGs, Python and SQL. Demand planning & analytics 1. Achieved $2.2M quarterly EBITDA by achieving 98.2% target across $22M Northwest India portfolio by planning day-level P&L forecasts and target allocation models across 15 financial metrics leveraging weighted trend analysis, and occasion clustering using tools like Python and SQL. 2. Reduced discount burn from 9% to 2.3% and saved 800+ man-hours annually by automating demand intelligence dashboards, real-time burn alerts, and RCA mailers, cutting festival analytics turnaround time from 4 days to 3–4 hours using ETL workflows, Superset, SQL, and Python. 3. Delivered 92% P&L projection accuracy for festival season across 20 occasions by building multi-view festival demand analytics and predictive forecasting models using occasion clustering, cuisine composition analysis, cohort behaviour leveraging analytical tools like Google Looker, Python and SQL.

Senior Data Analyst at JSW Energy Ltd, Mar 2024 - Feb 2025 · 1 yr, Hyderabad, 1. Saved $2M annually in projected forecasting and regulatory compliance costs across a 20 GW portfolio by building an in-house wind power prediction platform integrating SCADA, weather, and turbine health data across 192 turbines through automated reporting pipelines using Python and SQL 2. Achieved 68% wind power prediction accuracy by building XGBoost forecasting models using weather cohort engineering, turbine health state labelling, and feature engineering with scikit-learn in Python. 3. Reduced manual reporting effort by 37% by designing the energy department’s first centralized data infrastructure, automated SCADA-to-analytics pipelines, and real-time turbine performance dashboards using automated reporting workflows leveraging Excel, Python and SQL.

Data Analyst at magicpin, Dec 2022 - Mar 2024 · 1 yr 4 mos, Gurugram, 1. Saved $1.2M annually by reducing fraud cases from 500 to 25–27 per month through a hybrid fraud detection system combining rule-based logic and XGBoost with user, location, and transaction behaviour profiling, achieving 76% F1 score, 86% precision, and 69% recall using Python, XGBoost, and scikit-learn 2. Saved $217K monthly by improving transaction success rates by 12% and reducing user drop-offs by 7% through enhanced credibility checks, behavioural scoring, and real-time monitoring dashboards using data analytics and data visualisation tools like Python and SQL 3. Increased AOV by $700K/year and recommendation CTR by 8.7% across ONDC sellers by developing a hybrid collaborative filtering recommendation engine leveraging co-purchase behaviour analysis, taxonomy-based personalization, and probabilistic ranking logic to improve item discovery and reduce repetitive recommendations by using Python and scikit-learn.

Research Intern at Department of Computer Science, University of Copenhagen - DIKU, Sep 2021 - Oct 2021 · 2 mos, Denmark, 1. Worked on the “Privacy Lost on Educational Website and its Impact on Students and Learning” project. 2. Done data cleaning, feature engineering, and transformation on raw data collected from compromised websites during COVID-19 by segregating it into classification categories based on vulnerabilities and preparing it for ML modeling.

Education

Bachelor of Technology - BTech, Computer Engineering, Thapar Institute of Engineering & Technology