Sonali Singh

Sonali Singh

United States
3K followers 500 connections

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Activity

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Experience

  • Amazon Web Services (AWS) Graphic

    Amazon Web Services (AWS)

    Greater Boston

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    Greater Boston

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    Huntsville, North Carolina, United States

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    Boston, Massachusetts, United States

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    Thane, Maharashtra, India

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    Mumbai Area, India

Education

Licenses & Certifications

Courses

  • Advanced Data Science and Architecture

    INFO 7390

  • Algorithmic Digital Marketing

    INFO 7374

  • Data Management and Database Design

    INFO 6210

  • Data Science Engineering with Python for Machine Learning

    INFO 6105

  • Data Warehousing and Business Intelligence,

    INFO 7370

Projects

  • Hadoop Big Data Analysis of BTS Airline Data|

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    • Applied Map Reduce chaining algorithm to search for 10 most punctual airline carriers since 2003 with Hadoop
    • Computed the best months to travel for vacation by calculating total weather-related delays in Hive
    • Generated a list of most efficient airports in PIG by aggregating delays that could have been avoided

  • Value-based agent navigation in continuous world: Reinforcement Learning

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    ● Designed a simulation game where the agent must pick yellow bananas and ignore blue bananas through Reinforcement Learning
    ● Implemented a Deep Q-Learning model and tuned hyper parameters to maximize rewards

  • Movie Database

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    ● Designed ER Model that embodies the functionalities of movie database, normalized it to 3NF.Used
    Advanced SQL techniques to program various triggers to ensure data consistency and integrity.
    ● Scripted procedures, functions and views to generate complex data analysis reports. Used Tableau for
    data visualization

    See project

  • PowerBI dashboard for Price Optimization and Dynamic Forecasting for Nike Sales data

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    ● Collated distributed data from multiple stores and used K-Means to cluster these stores based on sales related attributes
    ● Trained a Random forest regression model to perform demand forecasting for different stores on a weekly basis
    ● Executed price optimization model for large data using PySpark clusters and created an Interactive dashboard using PowerBI and Tableau.
    ● Deployed our flask application on AWS EC2 , where we calculate the next purchase date and create a model for…

    ● Collated distributed data from multiple stores and used K-Means to cluster these stores based on sales related attributes
    ● Trained a Random forest regression model to perform demand forecasting for different stores on a weekly basis
    ● Executed price optimization model for large data using PySpark clusters and created an Interactive dashboard using PowerBI and Tableau.
    ● Deployed our flask application on AWS EC2 , where we calculate the next purchase date and create a model for weekly price optimization and dynamic forecasting .

    See project

  • Uncovering_Marketing_Insights

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    ● Analyzed marketing data using Salesforce Einstein analytics studio with Google CoLab and presented
    using an Interactive dashboard.
    ● Implemented marketing concepts like Cohort analysis, Customer segmentation using RFM and
    calculated LTV to suggest future actions.

    See project

  • Analyzing_Different_Marketing_Mix_Models

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    ● Analyzing promotional campaigns using Marketing Mix Modeling
    ● Developed a dashboard using Salesforce Einstein Analytics highlighting the relation between
    promotions campaigns and their effect on sales.

    See project

  • Bayesian_personalized_ranking_recommendation_systems

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    ● Implemented Bayesian Collaborative matrix algorithm to generate personalized recommender systems
    based on prior shopping habits.
    ● Created a demonstrative app using Streamlit and deployed over Heroku.

    See project

  • Implementing_Multiple_Attribution_Models using AWS pipeline

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    ● Comparing the affect of different attribution models and demonstrating the results using Panel
    ● Analyzed real world sales data to provide budget-ROI optimization by comparing different attribution
    models such as FTA, LTA, Time-Decay Attribution, Position based attribution ,Linear attribution, LSTM and LSTM with Attention models
    ● Created a pipeline using AWS EC2, S3 ,Glue crawler and Athena and visualized on Apache-Superset

    See project

  • Application of NLP on Dan Brown series

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    ● Developed a generic algorithm using NLTK’s Part-of-Speech tagger and Word Tokenizer along with
    SpaCy’s Entity Detector to determine the Protagonist of any book.
    ● Analyzed the similarities between summaries of the books using GloVe’s Pre-trained word vectors and
    Scipy’s Cosine distance model.
    ● Performed Sentimental Analysis on the books using Sklearn’s TF-IDF vectorizer, NRC’s word emotion
    lexicon and VADER’s Sentiment Intensity Analyzer.
    ● Visualized the…

    ● Developed a generic algorithm using NLTK’s Part-of-Speech tagger and Word Tokenizer along with
    SpaCy’s Entity Detector to determine the Protagonist of any book.
    ● Analyzed the similarities between summaries of the books using GloVe’s Pre-trained word vectors and
    Scipy’s Cosine distance model.
    ● Performed Sentimental Analysis on the books using Sklearn’s TF-IDF vectorizer, NRC’s word emotion
    lexicon and VADER’s Sentiment Intensity Analyzer.
    ● Visualized the acquired results using Word Cloud, Heat Map, Graphs, Stack Plot and Venn Diagrams.

    See project

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