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Geethanjali G

Senior Data Scientist

  • Chennai, TN
  • 6 years
Notice Period: 60 Days

    Candidate's About

    As a Senior Data Scientist with 7 years of experience, I have a strong background in leveraging data to drive insights and make informed business decisions. I am skilled in data analysis, machine learning, and statistical modeling. I have a track record of successfully implementing data-driven solutions and delivering actionable recommendations. I am adept at working with large datasets and using advanced analytics techniques to extract meaningful insights. I am

    Work & Experience

    S

    Senior Data Scientist

    Dec 19 - PRESENT

    Technology

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      Azure
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      Python
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      SQL
    • Provide leadership and expertise in data science, driving strategic initiatives and delivering actionable insights to support business decisions.
    • Develop and implement advanced statistical models and algorithms to solve complex business problems.
    • Collaborate with cross-functional teams to identify data-driven opportunities and develop innovative solutions.
    • Conduct d...
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    Root Cause Analysis– Excess Inventory

    Senior Data Scientist

    • Developed an RCA algorithm in Spark to identify excess inventory units and calculate their impact value ($). It runs daily for 1800 stores and 1M items with a runtime of approximately 30 minutes.
    • Automated an Excess RCA dashboard used by around 100 users to monitor overstock items at an item-location-day level. Provides overstock reasons, excess units/value at a loss, and consecutive days in excess.
    • The excess tool currently flags approximately 90% of item-locations, aiding in maintaining the overstock goal percentage.
    • Python
    • Spark
    • Tableau
    • Azure
    View Details

    Sales Anomaly Detection– To improve Forecast

    Senior Data Scientist

    • Developed a Sales anomaly detection model to identify, treat, and explain anomalies caused by disruptors. It captures 4% of anomalies, resulting in an 8% improvement in MAE of units at an item level.
    • Implemented a hybrid STL-ESD model using Pandas UDF over PySpark to account for items with different velocities. The model was scaled to all food categories and has a runtime of approximately 10 minutes.
    • The model effectively treats anomalies that result in severe over or under forecasts, contributing to maintaining a ~30% MAE.


    • Python
    • Azure
    • Tableau
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    Demand Transference– To Improve Assortment

    Senior Data Scientist

    • Led a 3-member team in delivering a POC to identify substitute items for a non-carry forward (NCF) and estimate demand transfer.
    • Identified substitute items using fuzzy logic (text-match), lift <10% in basket analysis, and factors such as price, demand, and store availability.
    • Built a regression model to gauge demand transfer percentage, achieving <=30% MAPE for 80% of items in the test category. Testing and scaling for other categories are required.


    • Python
    • Azure
    • Data Bricks
    View Details
    D

    Decision Scientist

    Feb 16 - Apr 19

    Technology

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      Azure
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      SQL
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      Python
    • Analyzed and interpreted complex data sets to provide actionable insights and recommendations as a Decision Scientist at Mu Sigma.
    • Developed statistical models and algorithms to solve business problems and support decision-making processes.
    • Collaborated with cross-functional teams and clients to identify data-driven opportunities and develop innovative solutions.
    • Pr...
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    Leading CPG Manufacture | Strategic Revenue Management- U.S

    Decision Scientist

    • Led an 8-member engagement of $2M, collaborating with Analytics, Trade Management, and Revenue Growth teams.
    • Developed a Trade Promotion Management (TPM) tool on a 3-tier architecture to identify key sales drivers and make data-driven decisions for maximizing unit sales, considering ROI and customer margin.
    • Powered the tool with a sales attribution model built for 80PPGs, leveraging factors like pricing and market competitors using Python libraries, achieving a median MAPE of ~15%.
    • Implemented Competitor Clash Avoidance to design promo plans aligned with forecasted competitor prices, resulting in improved price negotiations and a win-win situation with retailers, reducing 1000 hours of manual effort.
    • Python libraries
    • Spark
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    Artificial Intelligence

    Senior Data Scientist

    • Developed a gesture-controlled robot for intuitive and hands-free control of movement and actions.
    • Implemented vehicle-to-vehicle communication technology to enable seamless and efficient communication between vehicles.
    • Created an innovative solution that enhances user experience and improves coordination and communication between vehicles.
    • Leveraged advanced technologies and algorithms to enable gesture recognition and real-time vehicle communication.
    • Python
    • Tableau
    • Data Bricks
    • Azure
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    Global Sports Broadcaster| Digital Marketing- U.S

    Decision Scientist

    • Developed and deployed a Fan Based Affinity Model for soccer games, increasing revenue by 30% through emotion-based advertising targeted at accurate fan groups during live game broadcasts.
    • Built an ~85% accurate Classification - Logistic Regression model on ~80 million monthly users for soccer, categorizing them as High/Medium/Low/Not a fan for the next game based on online content consumption across platforms.
    • Utilized Scala-Spark to handle ~10 billion rows per day from Click Stream data, refreshing the consumption model daily with a model cadence of 15 days.
    • Scala
    • Spark
    View Details

    Education

    A

    Computer Science

    Anna University
    2012 - 2015
    H

    12th

    Higher Secondary School
    2011 - 2012
    S

    10th

    Secondary School
    2009 - 2010

    Achievements

    • Achieved a remarkable 8.9 CGPA at Anna University, showcasing exceptional academic performance.