Pratiksha Naik

Welcome to my Digital Portfolio

Experience

I am Pratiksha Naik, a data science professional with extensive experience in data analysis, business intelligence, and data processing across various industries, skilled in Python, SQL, R, and machine learning, with a proven track record of delivering innovative solutions and insights that drive business improvement and efficiency.

Education

MS in Engineering Science (Data Science)

August 2022 - February 2024

University at Buffalo, The State University of New York

Relevant Coursework: Statistical Learning and Data Mining, Data Intensive Computing, Introduction to Machine Learning, Data Model Query Languages, Numerical Mathematics, Probability Theory, Time Series Analysis

BE in Information Technology

August 2016 - October 2020

University of Mumbai

Relevant Coursework: Artificial Intelligence, Data Mining and Business Intelligence, Big Data Analytics, Database Management System, Advanced Data Management T echnology, Structured Programming

Professional Experience

Business Analyst

November 2024 - Present

Solenis | Hyderabad, TS, India

  • Design and develop interactive dashboards and reports in Tableau to provide actionable insights.
  • Utilize SSMS to manage databases, write efficient SQL queries, and optimize data extraction processes.
  • Act as a bridge between technical and business teams, translating business needs into technical solutions while ensuring alignment with organizational goals.

Data Scientist Volunteer

February 2024 - August 2024

University at Buffalo | Buffalo, NY, United States

  • Led development of a Blockchain Analytics Dashboard as part of Dr. Bina Ramamurthy's research team, enhancing capability to monitor and predict cryptocurrency trends.
  • Orchestrated data collection from multiple blockchains including Bitcoin and Ethereum, utilising APIs from 3 major blockchain explorers.
  • Developed Transaction Analysis module, using Python, PostgreSQL and Tableau to efficiently analyse and visualise transaction trends across over 500,000+ blockchain events.
  • Integrated ARIMA and LSTM models for cryptocurrency price forecasting, achieving 87% accuracy and reducing error by 12% across 5 cryptocurrencies over a 2-year period.

Data Analyst Intern

August 2023 - December 2023

Eitacies Inc | Santa Clara, CA, United States

  • Developed a virtual conference monitoring system to ensure professionalism and regulatory compliance, reducing non-compliance incidents by 34% in digital meeting spaces.
  • Pioneered development of a FLAN-T5 based tool for generating summaries of meetings, boosting user engagement insights by 12%.
  • Employed Computer Vision and Natural Language Processing libraries to analyze 100K+ images and text documents, improving content categorization by 17%.
  • Leveraged MongoDB to manage large datasets, efficiently handling over 2TB of data.
  • Crafted 10+ insightful and interactive visualizations in Tableau to improve client understanding and decision-making.

Data Processing Consultant

October 2020 – February 2021

Ugam Solutions (Now part of Merkle) | Thane, MH, India

  • Led collaborative efforts to process and assess market research data, tailoring insights to align with specific needs of 5+ clients.
  • Harnessed Python, SQL, and Alteryx for advanced algorithm development, accelerating query processing and enabling faster result delivery by 2 days on average.
  • Enhanced data accuracy and reduced processing time by 13% by employing Askia SAS for data management and analysis.
  • Efficiently managed and optimized databases handling over 8 million records in MySQL and PostgreSQL.
  • Drove a 2.7% sales increase for an international alcohol brand through demographic data analysis and strategic insight provision.
  • Presented complex data findings in 10+ high-stakes meetings, securing 2 long-term clients.

Projects

Fluence: Flu Shot Learning

Fluence is a web application leveraging machine learning to predict H1N1 and seasonal flu vaccination status based on demographics, health behaviors, and opinions.

Twitter Data Analysis To Identify Urban Issues

Analyzed Twitter data to identify and categorize urban issues in Mumbai, using machine learning algorithms to differentiate complaints from general tweets and visualize the most common problems faced by residents.

Songalytics: Spotify Data Analysis

This project involves analyzing Spotify data to understand music trends and predict song popularity, leveraging data science techniques for insights into listener preferences.

Emaily

Emaily is an AI-powered Streamlit app for crafting and replying to emails with ease.

24 Hour Backup

This Bash project creates a compressed backup archive of files modified in the last 24 hours from a specified directory to a chosen destination.

Foodo

"Foodo" is a mobile app designed to facilitate food donations by connecting donors with volunteers for pick-up and delivery to NGOs, aiming to reduce hunger and food waste.

Contact

Location:

Hyderabad, Telangana, India

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