Manoj M

As a store assistant responsible for system entry, I managed inventory data and updated product information. I ensured accurate records were maintained, facilitating efficient operations and inventory management.

As a store assistant at Unneco, I have been responsible for proficient inventory management and transaction processing. My efficient file handling has ensured smooth operations and exceptional service, optimizing customer relationships.

I managed to achieve over 90% accuracy in sales prediction by utilizing advanced time series analysis and predictive modeling techniques. The project involved integrating holiday markdowns and strategic planning to optimize the sales prediction process.

Leveraged time series and predictive models for store sales, integrating holiday markdowns. Advocated prioritizing business elevation through ruthless data manipulation, visualization, and strategic recommendations.

In this project, I implemented advanced machine learning algorithms and statistical models to forecast copper pricing with over 95% accuracy. The forecasting errors were reduced by 20% and pricing predictions were improved by 25%.

Achieved over 95% accuracy, reducing forecasting errors by 20% and improving pricing predictions by 25%.

The project involved optimizing the pricing strategy for Airbnb listings by improving pricing accuracy by 20%. Additionally, I reduced data processing time by 25% through efficient database management using MongoDB Atlas.

Boosted pricing strategy accuracy by 20%, slashing data processing time by 25% via MongoDB Atlas.

My role in this project involved developing an automated system for business card data extraction and generation using Python, Easy OCR, and PostgreSQL. The system significantly improved the process of information extraction and card generation.

Developed Python, Easy OCR, PIL for business card data extraction, SQL storage, and automated information removal enhanced cards.

My role in this project involved enhancing the speed and accuracy of data extraction from YouTube using Python and the YouTube API. The project achieved a 40% improvement in data extraction speed and ensured 95% accuracy in MongoDB.

Improved data extraction speed by 40% using Python and YouTube API, ensuring 95% accuracy in MongoDB.

Awarded for successfully completing the Advanced Programming course in Data Science from IITM.

Recognized for achieving proficiency in Information Technology by PCPC.

Awarded for successful completion of the Master of Data Science Program by Guvi.

Acknowledged for proficiency in SQL through the GUVI Certification program.