MANIDEEP PALLERLA

Versatile professional with expertise in data science, statistical modelling, and machine learning techniques, complemented by strong analytical thinking and problem-solving abilities. Proficient in big data handling, regression analysis, and device configuration, with a proven track record of delivering effective helpdesk support and exceptional customer service. Adept at leveraging organisational skills, adaptability, and time management to optimise workflows and drive results. Committed to applying advanced technical knowledge to solve complex challenges and contribute to innovative solutions.

• Leveraging Machine Learning for Malware Detection in Network Security, Developed an adaptable malware detection system using decision trees and SVMs to identify evolving and polymorphic malware with reduced false positives. Designed a real-time, resource-efficient solution suitable for large-scale networks, ensuring low latency and high scalability. Implemented advanced data preprocessing and continuous learning mechanisms to enhance detection accuracy and adaptability to emerging cyber threats.
• Leveraging Social Media Analytics to Enhance Sales Performance, Analyzed social media data to identify customer behavior patterns and optimize sales strategies. Developed predictive models using sentiment analysis and engagement metrics to forecast sales trends and improve customer targeting. Created dashboards for real-time monitoring of key performance indicators (KPIs), leading to data-driven decision-making and a measurable increase in sales performance.
• Face-Edge-Detection, Developed an advanced face detection and edge analysis tool leveraging OpenCV and skimage libraries. Implemented multiple edge detection algorithms (Canny, Sobel, Laplace, etc.) to extract key features from face regions in images. Designed segmentation techniques using K-Means clustering and Quickshift to enhance facial region analysis. Built a modular and efficient pipeline to integrate real-time face detection, edge mapping, and region segmentation for robust image processing.

British Airways Data Science Job Simulation on Forage - January 2025

• Completed a simulation focussing on how data science is a critical component of British Airways success
• Scraped and analysed customer review data to uncover findings
• Built a predictive model to understand factors that influence buying behaviour

Accenture North America Data Analytics and Visualization Job Simulation on Forage - January 2025

• Completed a simulation focused on advising a hypothetical social media client as a Data Analyst at Accenture
• Cleaned, modelled and analyzed 7 datasets to uncover insights into content trends to inform strategic decisions
• Prepared a PowerPoint deck and video presentation to communicate key insights for the client and internal stakeholders

BCG GenAI Job Simulation on Forage - January 2025

• Completed a job simulation involving AI-powered financial chatbot development for BCG's GenAI Consulting team.
• Gained experience in Python programming, including the use of libraries such as pandas for data manipulation.
• Integrated and interpreted complex financial data from 10-K and 10-Q reports, employing rule-based logic to create a chatbot that provides user-friendly financial insights and analysis.