Pritesh shinde

I’m an MSc Computer Science postgraduate focused on transforming raw data into meaningful insights through data analytics, machine learning, and business intelligence. I enjoy building data-driven solutions that are both accurate and usable for stakeholders.

As a Data Science Intern at Devtown, I processed and cleaned 50,000+ records to improve downstream data quality and reduce noise in analytical pipelines. I also applied feature selection and engineering to boost model accuracy by 15%, then translated regression and classification results into actionable business insights using Python and Scikit-learn.

At Cognifyz Technologies, I performed data wrangling and transformation with Pandas, NumPy, and SQL, reducing data inconsistencies by 30%. I built and validated predictive models reaching ~80% accuracy, and created BI dashboards and KPI reports with Matplotlib and Seaborn to support senior stakeholders’ decision-making.

My projects extend this work into real applications, including a Streamlit object detection web app combining YOLOv8 and OpenCV and a resume screening automation tool using NLP for candidate shortlisting. I’m excited to bring the same rigor—data cleaning, feature engineering, and clear visualization—into Data Analytics, BI, or Data Science roles.