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Full Stack Developer
Location Bangalore
Total Views51
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Member since30+ Days ago
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Contact Details
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Candidate Information
  • User Experience
    Experience 4 Year
  • Cost
    Hourly Rate$5
  • availability
  • work from
    Work FromOffsite
  • check list
    CategoryInformation Technology & Services
  • back in time
    Last Active OnMay 08, 2024
Key Skills
Node.JSMySQLReact JSJavascripttypescriptPostGre SQLMongoDB


• Participated in discussions with business stakeholders to design, develop, and implement machine learning models and an Interaction UI for the user decisions in the Retail/CPG domain.

• Built a recommendation system (SKU Simplification) to streamline the delisting process for underperforming SKUs, resulting in a 10% reduction in production costs.

• Implemented the solution using Python, PySpark, Spark SQL on Azure Databricks, and scaled it globally to different markets and verticals, saving the client 15% in logistics and warehouse costs.

• Improved the data availability of the sales and performance of SKUs through the system at one place by at-least of 50% globally and more than average when individual markets from countries having better data coverage.

• Developed a Backend and Front-End System using NodeJs, ReactJs with Typescript and Javascript in building the UI and Server to record user decisions and convey the model results properly.

• Mentored and lead a group of 4 in building, analyzing and execution of the system. OCT 2019 – DEC 2021 SENIOR ENGINEER, MINDTREE LIMITED

• Built a B2B E-Com Marketplace for Pharma client in getting the Small Scale Hospitals a better deal of pharma prices with leading suppliers in the market using NodeJs, React, TypeScript, MongoDB with a Micro Services architecture.

• Utilized Python, PySpark, Spark SQL on Databricks to analyze and model data.

• Reported key findings, such as purchase behavior and profitability, to improve the impact of data modeling on business and presented these findings using data visualization techniques.

• Developed predictive models using supervised machine learning algorithms to predict customer replenishment and increase repeat purchases, resulting in a 78% accuracy rate. 2

• Designed and executed an end-to-end data pipeline for processing, modeling, and deploying results into cloud storage and SFMC for marketing, resulting in a minimum of 2x improvement in marketing efficiency.

• Received A-Team Award and Hats-Off for the contributions of the team and successfully delivering the projects.

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