Data Analyst with 1+ years in Data Analysis & Machine Learning.
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Experienced Data Analyst and MIS Executive with 1.5 years of experience, specializing in data analysis, visualization, and machine learning. Proven ability to streamline data collection processes, analyze complex datasets to identify patterns and trends, and develop predictive models. Proficient in Python, SQL, R, Power BI, and various AI tools like ChatGPT and Claude. Skilled in collaborating with teams to deliver actionable insights and improve services, with a strong background in business analytics.
Bengal Institute of Business Studies – Vidyasagar University
MBA · Business Analytics & Data Science
August 1, 2023 – June 30, 2025
Techno India University
BBA · Marketing
August 1, 2017 – June 30, 2020
National English School
ISC · 12th Board Exam
June 1, 2015 – May 31, 2017
National English School
ICSE · 10th Board Exam
June 1, 2014 – May 31, 2015
Sooti Textiles
Data Analyst / MIS Executive
February 1, 2026 – Present
Kolkata, West Bengal, India
TrackBee Data Solutions
Data Analyst Intern
August 1, 2024 – January 1, 2025
Kolkata, West Bengal, India
mPokket
Junior Associate
March 1, 2021 – January 1, 2022
Kolkata, West Bengal, India
MIS Systems at Sooti Textiles
June 24, 2026 – Present
Designed daily, weekly and monthly report making system in the Google sheets with the help of Claude, ChatGPT and Zapier. Created HTML and Google Forms, linked them to the Google sheets and designed system so that the fetched data gets cleaned automatically, placed in the required fields, perform auto-calculations as per the requirement of the reports. Created an ERP system which can generate reports automatically through just by collecting data from various departments, used PostgreSQL to store large datasets and used MS PowerPoint and Power BI to make reports on Monthly basis.
Diabetes Prediction Model
June 24, 2026 – Present
Cleaned and separated the feature and target columns from the dataset. Used StandardScaler technique to scale the features and implemented Support Vector Machine algorithm for prediction. The model showed an accuracy score of 78%.
Car Price Predictor Project
June 24, 2026 – Present
Used OneHotEncoder for helping the model to identify different categories and utilized column_transformer for creating pipeline. Implemented LinearRegression algorithm and used r2_score for accuracy score which initially showed 61% accuracy. Increased the accuracy score to 84% by performing feature engineering.
Movie Recommender System
June 24, 2026 – Present
Performed data cleaning by removing duplicates and null values from the dataset and merging the required datasets. Fetched the columns which are textual while removing the numerical columns. Implemented CountVectorizer, PorterStemmer and cosine_similarity functions to create the recommender system.
Machine Learning
IBM
February 24, 2024 – Present
Machine Learning
IIT-Kanpur
January 15, 2024 – Present
Data Visualization
IBM
September 23, 2023 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from MIS systems to predictive models and recommender systems, indicates a broad interest in data-related challenges. The blend of professional and personal projects, along with certifications, shows a commitment to continuous learning and skill development. The current role as a Data Analyst / MIS Executive aligns directly with the target role, suggesting a strong cultural fit for a data-driven organization. The use of AI tools in professional projects also highlights an adaptability to modern technologies.
Soft Skills & Operational Fit
The candidate's experience at Sooti Textiles and mPokket indicates an ability to work with clients, manage operational data, and contribute to MIS teams. The description of designing systems to minimize discrepancies and streamline processes suggests a proactive and problem-solving approach. Collaboration with McKinsey & Company during an internship also points to an ability to work in structured, high-demand environments. The candidate's current role as a Data Analyst / MIS Executive aligns well with the target role, demonstrating operational fit.