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Jewel JJames

-Data & AI Consultant-

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About Me

Jewel is a senior consultant in the Data & AI practice at Deloitte with expertise in data engineering who is passionate about creating data-driven solutions. Experienced in designing scalable data architectures, implementing advanced analytics, and collaborating with stakeholders. Skilled in project management, client engagement, and continuous learning. Passionate about driving data-driven transformations for business success.

Experience

Deloitte

Senior Consultant

  • Developed meta-data-driven ingestion pipelines to ingest data from various sources into the SQL database.
  • Designed Data relationship model for the showcasing transformation of the source to output templates
  • Designed and implemented error-handling mechanisms to capture and handle exceptions and data quality issues during the pipeline execution.
  • Created and tuned ETL mapping and underlying workflows to optimize the data load and performance. Responsible for publishing the Talend jobs to cloud, configured monitoring and scheduled job for runs
  • Developed complex conditional expression in JAVA to implement business rule.
  • Led Design workshop with SAP SMEs and key stakeholders for one of the complex deliverables in Data Migration SOW
  • Developed complex T-SQL queries and views to address gaps in source data and manipulate it effectively.
  • Provided coaching and guidance to a team of developers, helping them leverage Talend's features effectively for building scalable and maintainable data ingestion pipelines.
  • Led a team of 5 in implementing business rules focused on the data transformation part of the solution
  • Played a key role in defect triaging and Communicating key activities, responsibilities, and timelines to respective business owners.
  • Actively hosted Scrum ceremonies such as sprint planning, retro and daily stand-ups.
  • Created a power app facilitating comment capture for internal asset enhancement.

Amazon

Analyst

  • Extracted and processed vast amounts of data from diverse sources, employing Python and SQL scripting
  • Delivered accurate, high-quality data with granular-level accuracy, surpassing 100 million rows with strict deadlines
  • Identified the valuable information within the unstructured data and transformed it in a tabulated form to enable further analysis.
  • Performed descriptive and prescriptive analyses on retail data, enabling customer profiling.
  • Developed a reporting tool for showing valuable information to the stakeholders.
  • Communicated reports and work completed with project stakeholders
  • Contributed significantly to the Product Compatibility Platform team, yielding an incremental turnover of $9 million in 2015.
  • Provided oversight by reviewing daily status updates and tracking analyst progress.
  • Experience in taking over 25+ technical interview rounds. Conducted over 25 technical interview rounds, showcasing expertise in assessing candidates' technical capabilities.

Education

RMIT University

(Australia) Feb 2019 - July 2021

Master of Data Science

Awarded Masters's 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

Project Showcase

Project DeCarbo

Project DeCarbo is an innovative Web-App, creating personalized green portfolios for individuals and businesses, assessing carbon footprints and offering tailored eco-friendly recommendations. It empowers users to make sustainable choices, explore greener areas, and set goals while earning Green Points for rewards like loan advantages and tax incentives. It's a movement toward an environmentally conscious world where sustainability is both encouraged and rewarded..

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The Zeroo app

The Zeroo app employs a machine learning model to predict user purchase patterns, offer tailored product recommendations, and minimize food wastage. Users input product details and expiry dates, receiving reminders and the option to donate to nearby NGOs. Donations trigger notifications, aiding NGO inventory planning, while users receive tokens for discounts on future purchases.

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Energetik

Energetik offers users insights into energy consumption and charges, utilizing time-series forecasting for future usage and bills. They compare individual and neighborhood consumption, aiding relocation decisions. A reward-based system encourages eco-friendly usage, while a credit-based payment scheme assists during COVID-19, using tokens for bill payment.

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Insightopedia

"Insightopedia App" aids governments in analyzing unemployment trends, correlating demographic factors, and informing effective policy decisions for targeted investments, thereby striving to lower unemployment rates and enhance global living conditions.

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Trash to Cash

Introducing a Trash to Cash App based on subscription and circular economy models. Users lease devices, can donate old ones for NGO tokens, promoting eco-friendly behavior. Manufacturers sell e-waste to recyclers, fostering a circular economy. Platform tracks revenue and carbon footprint for transparency and sustainability.

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Stance Classification in Tweets using NLP

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Classify Images of Road Traffic Signs

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Satellite Intelligence Sugarcane Harvest Forecasting Model

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Covid-19 Analytics Web App

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UniLodge Management System

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Skills

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