Ranjan Das

A working professional of 3 years of experience having keen interest to learn and bridge evolving skills in the field of Data Science. Currently, as an System Engineer I work with both Frontend And Backend technologies to develop, build and test modern Web Applications and as an Open Source Contributor, I enjoy the moments that bring new learnings and sharing knowledge to others.

I have completed my graduation in Electronics and Communication Engineering from Techno Main Salt Lake. Since few years, I grow up with technologies in the domain of Data Science and Machine Learning and I'm very much interested for new opportunities under this domain which show the potential to use my skills to ideate creative contexts and illustrations.

• Achieved TCS Gems by completing 100% Accessibility Compliance - AODA for Canada Clients for the product within a short time span of development and delivery turnaround time with accuracy and efficiency.
• Become a Contextual Master at TCS to evolve and deliver innovative solutions, accessibility compliance, and process improvements

• Machine Learning Training from IIT Bombay - 2 Months

Brazil E-commerce Business Case Analysis(SQL Google BigQuery)
Aug 2025 - Present

• Queried and processed 100k+ e-commerce records in SQL (BigQuery) to uncover customer behavior and order trends.
• Pinpointed seasonal demand peaks and top regions, enabling 15% uplift in targeted marketing performance.
• Built and presented a Tableau dashboard/report that optimized logistics, improving delivery efficiency by 20%.

Skills: SQL · Data Analysis · MySQL · Exploratory Data Analysis

Netflix Data Visualization using Python Libraries
Apr 2025 - Present

• Examined Netflix content library with Python (Pandas, NumPy), revealing that 70% of content is movies.
• Recommended expansion of TV shows and optimal release timing during Indian holidays, driving higher retention potential.
• Visualized viewing trends with Matplotlib & Seaborn, enabling data-driven content strategy decisions.
• Delivered audience engagement insights that informed programming and marketing strategies.

Skills: Data Visualization · Python (Programming Language) · Data Analysis · Seaborn · Pandas · NumPy · Matplotlib

Walmart: Confidence Interval and CLT

Jun 2025 - Aug 2025

• Conducted statistical analysis on Walmart sales data using Python, Pandas, NumPy, and CLT methods.
• Built 95% confidence intervals to estimate weekly sales, detecting a 15% holiday sales spike and
  regional/store-type variations.
• Designed data visualizations (Seaborn, Matplotlib) to communicate sales patterns, supporting leadership
  in strategy planning.Conducted statistical analysis on Walmart sales data using Python, Pandas, NumPy, and CLT methods.

Skills: Statistics · Probability · Probability Theory · Python (Programming Language)

Delhi House Price Prediction ML Model (End to End Development)

Oct 2020 - Dec 2020

• Developed a Machine Learning model on Delhi House Price Prediction (with an accuracy more than 80%) using Kaggle dataset and by applying One - Hot Encoding and Linear Regression ML algorithms to our raw dataset for training purposes after data preprocessing and deployed the saved Model over Web platforms after demonstrating it with HTML5, CSS3, Bootstrap 4 and other web development languages and technologies.

Skills: Machine Learning · Python (Programming Language)

YouTube Adview Prediction Model using Machine Learning

Oct 2020 - Dec 2020

• Prediction of the target variable which is set as adview column after the analysing the correlations between the other parameters which are likes, dislikes, comment, duration, category etc. and deployment of the model in different user interfaces or platforms as an useable product.Prediction of the target variable which is set as adview column after the analysing the correlations between the other parameters which are likes, dislikes, comment, duration, category etc. and deployment of the model in different user interfaces or platforms as an useable product.

Skills: Machine Learning · Python (Programming Language)

Email Spam Classifier using Machine Learning

Aug 2020 - Oct 2020

• Developed an email Spam classsifier app which can predicts whether an email is fake or not by analysing the data present in that particular email's body using Machine Learning algorithm and text vectorization technique.

Skills: Machine Learning · Python (Programming Language)

Loan Prediction Model using Machine Learning

Jun 2020 - Jul 2020

• Developed Machine Learning model which is built by training our raw inputted datasets using Linear Regression and Logistic Regression ML algorithms and saving the model with the help of python's pickle and joblib module for further demonstrations over the web or app or other equivalent platforms in practical use.

Skills: Machine Learning · Python (Programming Language)

Data Science and BA Intern 

The Sparks Foundation

• Worked on prediction using Supervised, Unsupervised Learning, and Decision Tree Classifier for cluster classifications and demonstrations, and computed Exploratory Data Analysis (EDA) on Super Store Data to find insights.

Machine Learning Intern

Internship Studio

• Developed YouTube Adview Prediction model to predict the target variable adviews of any content after analyzing the correlations.