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Data Science with less than a year in Applied Machine Learning & Optimization
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Assessing your cultural and operational fit
M.Sc. Mathematics graduate with hands-on experience in Applied Machine Learning, Optimization, and AI-driven systems through internships and academic projects. Skilled in Python, PyTorch, SQL, and data-driven decision modeling, with experience building predictive ML and real-time intelligent applications. Familiar with optimization techniques, simulation-based evaluation, and agentic AI coding workflows for rapid prototyping and experimentation. Passionate about solving real-world operational and decision-making problems using ML and Deep Learning.
Central University of Kerala
M.Sc. Mathematics · Mathematics
September 1, 2023 – May 1, 2025
Kannur University
B.Sc. Mathematics · Mathematics
November 1, 2020 – April 1, 2023
Luminar Technolab
Data Science Intern
June 1, 2025 – February 1, 2026
Cochin, Kerala, India
Cake Cost Optimization Without Loss of Quality
June 1, 2025 – Present
Developed a predictive ML and optimization system to minimize ingredient cost while maintaining product quality constraints. Built a Random Forest model to estimate quality scores based on ingredient composition and implemented a constraint-based optimization workflow to identify cost-efficient formulations. Designed evaluation experiments to compare optimized vs baseline configurations and deployed the solution using Streamlit for interactive scenario testing.
Student Attention Monitoring System
June 1, 2025 – Present
Built a real-time intelligent monitoring system using Python, OpenCV, and MediaPipe to detect attention-related behaviors including drowsiness, head direction, face absence, and mobile phone usage. Designed rule-based decision logic and alert mechanisms using facial and hand landmark analysis. Evaluated system responsiveness under multiple real-time scenarios and optimized processing for continuous webcam inference.
Meta (Facebook & Instagram) Ad Performance Dashboard
June 1, 2025 – Present
Designed and developed an end-to-end Power BI dashboard to analyze digital marketing campaign performance across Meta platforms. Processed and cleaned raw ad data using Power Query, built an optimized data model and created DAX measures to calculate KPIs such as CTR, CPC, CPA, impressions, reach and conversions. Implemented interactive slicers, filters and visualizations to compare campaign, ad set, and platform-level performance, enabling data-driven marketing optimization and decision-making.
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of applications for data science, from real-time monitoring systems to business intelligence dashboards and optimization problems. This breadth of interest suggests adaptability and a willingness to tackle varied challenges. The focus on practical application in projects aligns with a results-oriented culture. However, with only academic projects and one internship, the extent of experience in collaborative, fast-paced industry environments is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems independently and a structured approach to problem-solving (e.g., designing evaluation experiments, optimizing processing). The internship experience suggests an ability to contribute to data analysis and model building tasks within a team context. However, without direct interview data, assessing specific soft skills like teamwork, leadership, or conflict resolution is not possible.