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Jewel James

-Data Analyst | Bussiness Analyst-

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About Me

I believe that with the amount of data available (and constantly generated) today, one can make a positive impact to better the lives around us. Aspiring to be a good Data Scientist and a better person everyday.

I hold a Bachelor’s (Computer Science) and Master’s degree (Data Science) and a 3+ years of track record of analysing business intelligence reports and data that are extracted from different sources in the retail domain with ability to make data driven decisions and convey insights via compelling storytelling presentations. Proven knowledge in expanding existing data collection and data delivery platforms. Worked extensively in development report and maintenance of analytical projects using Python, Java, SQL and PowerBI tools.

Experience

Amazon

Business Intelligence Analyst

  • Extracted and cleaned data from reports, databases, etc and applied different text mining techniques using Python and SQL scripting.
  • Delivered huge volumes of data with granular level accuracy within strict deadlines. (100 Million+ rows of data)
  • Executed successful migration and reporting of key metrics derived from data handled by the expansion team.
  • Identified the valuable information within the unstructured data and transformed it in a tabulated form which can enable further analysis.
  • Performed descriptive and prescriptive analysis on retail data for a customer profiling.
  • Developed a reporting tool using POWER BI for showing valuable information to the stakeholders.
  • Communicated reports and work completed with project stakeholders
  • Contributed significantly to the Product Compatibility Platform team, which made an incremental turnover of $9 Million in 2015.
  • Review of daily status updates and tracking of the analysts.
  • Contributed significantly to the Product Compatibility Platform team, which made an incremental turnover of $9 Million in 2015.

180Degree Consultancy

Consultant

  • Provided client with information regarding partnership opportunities in interstate youth career counselling programs.
  • Collaborated with team members and client to dissect and analyze project requirements.
  • Conducted extensive desktop research to uncover the best opportunities available for the client.
  • Communicated complex insights in a persuasive manner via data visualization and professional pitches.
  • Adopted the Design Thinking approach (and implemented User Story and Journey Maps) to understand key stakeholders’ wants and needs.
  • Delivered a professional business pitch to the client representatives and industry partners.
  • Quality control and compilation of deliverables with final reports presented to client.

SarasCare

Data Science Intern

  • Formulated the problems statement such that it should add value to the business.
  • Developed and deployed python-flask based web application(chatbot) from scratch.
  • Figured out the advantages and limitations of examined models and made decision on which model to implement in production.
  • Explored and analysed dataset before inputting it in the model.
  • Applied NLP model to the dataset for predicting the severity of the cases.
  • Implementation of Open AI GPT 3 ,SimCSE Bert and the Crude Classifier model.
  • Figuring out the future scope, advantages and limitations of examined models.
  • Developed and deployed python-flask based web application(chatbot).
  • Deployed application in Microsoft azure as per client requirement.

Education

RMIT University

(Australia) Feb 2019 - July 2021

Master of Data Science

Awarded Masters degree with Distinction

Anna University

(India) June 2011 - April 2015

Bachelor of Engineering in Computer Science

Completed bachelor of engineering degree in computer science under the faculty of information and communication engineering and placed in First class

Projects

Stance Classification in Tweets using NLP

This project was undertaken to do stance classification of tweet and discovering the best fitting deep learning model that can successfully classify stance (FAVOR, AGAINST, NONE) based on particular Target (topic) about a tweet.Final selection was made of LSTM model as they proved to work best in natural language processing scenario. Analysing intra variability of classes and imbalancing of data, efforts were taken to choose a balanced data set for training purpose. glove MODEL trained on wikipedia data was used .The data was transformed to task vocabulary to fit the model. The model after large iterations of fine tuning made it robust and provided an accuracy score on validation as 52.97 and test score as 53.8 respectively.

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Classify Images of Road Traffic Signs

This project was undertaken to discover the best fitting machine learning model which can successfully classify images based on two factors, namely shape and labels. Three different ML model development techniques were employed : MLP, CNN . The CNN model proved to be highly accurate .Analysis of intra variability of classes and comparison of classification performance of four Convolutional Neural Networks based on parameter tuning gave us the optimal model. The images provided are grey scaled and sized to a 28*28 density. The development of the model has three stages: image preprocessing, detection, and recognition. The model demonstrated a promising result with an accuracy of 81 %for shape classification and 62% for label classification. Independent evaluation was done by collecting images from internet sources and real time clicks of victorian, Melbourne streets.

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Satellite Intelligence Sugarcane Harvest Forecasting Model

95% of Australian sugar is grown in Queensland, and sugarcane is the second-highest export crop after wheat as it contributes 2.5 billion dollars to the Australian economy. Developed the time series model (FB Prophet) to forecast the overestimation and underestimation of sugarcane for sugar mills using Satellite imagery datasets of sugarcane fields at Queensland. Processed the image data using python libraries and Google cloud services and also merged that dataset with weather and soil quality datasets to find the correlation and improve the performance of the model.

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Covid -19 Analytics Web App

Developed an application using Amazon web services and extends a Web system to add business functionality. The environmental setup was done using elastic beanstalk where the backend was developed using NodeJs. The virtual server was launched through the EC2 instance and NoSQL database mongo DB was used for data storage. A complete user profile authentication was set up using amazon cognito.

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UniLodge Management System

Developed a housing rental system using Java programming language with the help of Eclipse IDE. Also to make records accessible via Java JDBC technology. This is a simple yet complete hotel management system. This system performs all the necessary tasks that a hotel software application performs. JavaFx was used to tailor make the Graphical User Interface. Text file handling was implemented in the program to import and export data to facilitate analysis.

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Skills

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