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  • Viewed 32


  • 2023 - 2024
    University at Buffalo, The State University of New York

    Master of Science in Data Science

    Courses: Machine Learning, Computer Vision, Deep Learning, Statistical Learning, Data Mining, Database Systems

  • 2015 - 2019
    Indian Institute of Technology Roorkee, Roorkee, India

    Bachelor of Technology in Engineering

    Relevant Courses: Computer Programming, Data Structures and Algorithms, Optimization Techniques


  • 2022 - 2023
    SIGMOID, Bangalore, India

    Associate Lead Data Scientist

    Reckitt – eCommerce Advertising | Seaborn, XGBoost, Statsmodels
    • Developed an AI-powered advertising solution, boosting Amazon ad performance & increasing purchase rates by 60%
    • Created XGBoost model to identify best performing line items in a campaign based on CTR & PPD & Impressions
    • Improved the Return on Ad Spend (ROAS) 10x by optimizing the advertising cost structure using the model

  • 2019 - 2022
    FRACTAL ANALYTICS, Bangalore, India

    Data Scientist

    EU Price Optimization | Azure Data Lake, Databricks, Bayesian Regression, PyGAD
    • Developed an ensemble of Genetic Algorithm, Particle Swarm Optimization, and Differential Evolution models
    • Designed the objective function using KPIs like Turnover, Risk, Gross Profit & Gross Margin to get the best prices
    • Implemented Bayesian Regression models for product-level price elasticities with MAPE 70%
    • Automated the process flow of retrieving data from Data Lake & pre-processing through data pipelines on Azure
    Edge Analytics | Pyspark, Blobs, Data Lake, Azure Data Factory, SQL Server, Azure Analysis Services, Azure Devops, Git
    • Implemented automated ETL workflows in the Azure cloud to analyze the performance of offers given to retailers
    • Configured SQL data warehouse and created tabular data models in Azure Analysis Servicesfor Power BI reporting
    • Reduced the time taken to run the process of analyzing promotional spends by ~50% with zero manual intervention
    Darwin Intermediate Station | Azure Blobs, Azure Data Lake, Python, MySql Workbench, Putty, Apache Airflow, CI/CD
    • Implemented an intermediate storage, utilizing Azure Blobs & Data Lake & SQL database to process the POS data
    • Transitioned the reporting system from monthly to daily updates, enabling quick decisions & decrease in data loss
    • Created data pipelines using python scripts to do preliminary checks on the raw data and provided feedback
    Salesman Incentive Optimization | R, gtools, ggplot, dplyr
    • Designed an automated tool that staged preprocessing & 20,000 regression models runs against business targets
    • Consolidated data from data sources & utilized stepwise regression to identify the top contributing features/KPIs
    • Recommended top KPIs & their optimal values using the inflection point in graphical visualization of each KPI plot