Abhishek Jaiswal

As a Junior Data Scientist, I have worked on several projects, including designing data pipelines using Big Data technologies like Hadoop, Airflow, and Amazon Lambda functions. I have also gained two years of experience in data analysis using Power BI and Tableau, where I analyzed data to provide insights into business operations. In addition, I have productionized ML pipelines using GCR and GKE, and I have implemented Multi-GPU architecture to optimize training time for machine learning models.

My expertise in statistical concepts has enabled me to evaluate and normalize data and identify Principal Components, which facilitates the ease of training models while maintaining their efficiency. I am also skilled in designing end-to-end ML applications and deploying them using Docker and Kubernetes engine.

Data Science Intern | National Fair Housing Alliance, Washington DC Jun 2022 - Sept 2022

Data Analysis & Engineering:

• Automated an ETL/ELT pipeline to fetch Twitter posts using Tweepy and AWS lambda function and store it in S3 bucket
• Performed Sentiment Analysis on the filtered tweets to analyze the impact of Fair Housing Acts on people of different community
• Conducted in-depth Exploratory Data Analysis on demographic data to draw insights related to Housing Discrimination cases
• Presented the Patterns and Insights to organization’s leadership contributing towards informed decision making
• Designed an ETL pipeline to web-scrape data using AWS lambda, Docker and BeautifulSoup reducing manual effort by 25% 
• Gathered insights on discrimination in real estate to generate a report and supporting evidence to influence policy-making

Data Science:

• Boosted member base expansion by 35% by designing and automating an NLP-based recommendation system using AWS EC2 and CRON jobs to provide personalized suggestions based on user interests every week 
• Used LDA and STTM to effectively cluster Newspaper articles & Twitter post via Topic Modeling and uncover important insights

Software Engineer | LTI (L&T Infotech), Mumbai  Nov 2018 – Aug 2021

Data Analysis & Engineering:

• Utilized Power BI to extract and analyze supply-chain data from MS CRM and MS NAV across 24 different data warehouses
• Improved the accuracy of Sales Forecast reports by 25% empowering Sales and Requisition teams with actionable insights
• Performed comprehensive analysis of least active accounts to reconcile repair costs from projects improving annual turnover
• Discovered $30,000 from previously unaccounted accrued revenues accounting to increase in profit and turnover for the team
• Extracted data from disparate sources using intricate SQL queries to fulfill ad-hoc reporting requests using MS SSMS & PowerBI
• Designed an AI model using Powerapps to authenticate customer using document OCR reducing manual errors by 70%

ERP Developer:

• Led a team of 6 professionals to develop an E-procurement portal using Java & Angular and adhering to the AGILE methodology 
• Build an app to streamline & automate Loan Approval and Disbursement using MS Power Platform improving efficiency by 40%
• Leveraged Data Analytics to identify frequent client issues and suggested practical workarounds reducing daily issues by 30%
• Reduced deployment errors by 80% via an ERP deployment workflow for ERP apps on Azure & AWS using Power Automate
• Organized and cleaned data from large datasets aiding statistical modeling to identify KPIs and uncover meaningful insights for stakeholders to create Business impact 
• Collaborated with cross-functional teams such as finance, operations, marketing, and sales to develop data-driven solutions to address their business challenges

Data Science Intern | National Fair Housing Alliance, Washington DC Jun 2022 - Sept 2022

Data Analysis & Engineering:

• Automated an ETL/ELT pipeline to fetch Twitter posts using Tweepy and AWS lambda function and store it in S3 bucket
• Performed Sentiment Analysis on the filtered tweets to analyze the impact of Fair Housing Acts on people of different community
• Conducted in-depth Exploratory Data Analysis on demographic data to draw insights related to Housing Discrimination cases
• Presented the Patterns and Insights to organization’s leadership contributing towards informed decision making
• Designed an ETL pipeline to web-scrape data using AWS lambda, Docker and BeautifulSoup reducing manual effort by 25% 
• Gathered insights on discrimination in real estate to generate a report and supporting evidence to influence policy-making

Data Science:

• Boosted member base expansion by 35% by designing and automating an NLP-based recommendation system using AWS EC2 and CRON jobs to provide personalized suggestions based on user interests every week 
• Used LDA and STTM to effectively cluster Newspaper articles & Twitter post via Topic Modeling and uncover important insights