Data Engineer @ Accenture || Ex-Tredenc || Data practitioner || Exploring Open Source || Forever a problem solver
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Accenture
Data Scientist
June 25, 2026 – Present
e2e-nlp-app
January 16, 2023 – January 16, 2023
An end-2-end nlp project leveraging various concepts
View Projectstreamlit_sf_app
November 22, 2022 – November 22, 2022
My first streamlit app leveraged over snowflake❄️ and python🐍
View ProjectRetail-Data-Analysis
August 1, 2022 – August 1, 2022
Retail data of various stores under Tesco is analyzed in Excel and PowerBI. Tesco PLC is a British multinational groceries and general merchandise retaile
View ProjectPinterest-automation
June 23, 2022 – June 23, 2022
This repo contains python scripts to automate pin creation in pinterest.
View Projectprevious-bnomial-questions
April 12, 2022 – May 19, 2022
One stop platform containing questions from bnomial
View ProjectNameExtractor
November 19, 2021 – November 21, 2021
Build using Flask. The main motive of this api is to extract the name and filename of the uploaded file name and display them.
View ProjectTwitter-Sentiment-Analysis
August 16, 2021 – August 21, 2021
Beginner Project to enter into the world of Natural Language Processing
View ProjectSports-Popularity-Forecast
April 15, 2021 – September 17, 2021
This project is to measure the popularity of each league using the search data collected from Google Trends, which give real-time historical data on search words. With this project, it is also possible to compare and forecast how the sports league are trending with respect to each other using three models — trend plus seasonality regression, Holt-Winters Multiplicative (HWMM), and Seasonal Autoregressive Integrated Moving Average (SARIMA). Businesses interested in advertising or investing with either league may leverage these forecasts for deciding which sports league provides the greater or long-term value.
View ProjectCultural Fit Analysis
The candidate's projects show a proactive, self-driven approach to learning and applying data science concepts. The diversity of personal projects (NLP, forecasting, automation, data analysis) indicates a broad interest within the data science domain. However, the lack of team-based projects or contributions makes it difficult to assess collaboration and cultural fit in a professional team setting.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.