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AI Engineer with less than a year in Data Analytics & Machine Learning
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B.Tech Artificial Intelligence & Data Science undergraduate with strong analytical capabilities and hands-on experience in data analytics, machine learning, and business data reporting. Proficient in Power BI, Tableau, MS Excel, Python, and SQL, with demonstrated ability to process large-scale datasets, identify data anomalies, generate actionable insights, and build interactive dashboards. Experienced in backend data pipelines and real-world analytics projects spanning distributed computing, predictive modelling, and graph analytics. Seeking a Data Analytics Internship to apply data-driven problem-solving and reporting skills to business audit and engineering analytics challenges.
Amrita Vishwa Vidyapeetham
Bachelor of Technology · Artificial Intelligence & Data Science
August 1, 2023 – Present
Shristhi School
Higher Secondary · Bio-Mathematics
June 1, 2022 – May 31, 2023
Amrita Mind Brain Center, MoE Virtual Labs Initiative
Research Intern - Biomedical AI & Backend Engineering
January 1, 2026 – April 1, 2026
Kollam, Kerala, India
Hybrid Centrality-Guided GNN for Influential Node Ranking
February 1, 2026 – May 1, 2026
Built a hybrid analytical framework combining 8 graph centrality metrics with GraphSAGE-GAT node embeddings and XGBoost regression for scalable influence ranking on the Facebook SNAP dataset (4K+ nodes, 88K+ edges). Achieved 0.9169 Spearman correlation and 0.9228 R2, with zero-shot generalisation on unseen Email-EU and WikiVote networks and inference optimised to 8 ms per query. Outperformed all traditional single-centrality baselines, demonstrating the value of learned graph representations and rigorous quantitative model evaluation over heuristic node-ranking approaches at scale.
View ProjectPageRank on Large-Scale Web Graph - Distributed Analytics
September 1, 2025 – November 1, 2025
Engineered an end-to-end distributed data analytics pipeline on a 4.8M node, 69M edge graph dataset, computing PageRank and authority metrics end-to-end in 238 seconds using Apache Spark and Hadoop HDFS. Applied MLlib clustering algorithms and built interactive convergence dashboards, translating raw internet-scale graph data into structured, business-readable analytical reports for authority-node identification. Optimised distributed memory execution and iterative graph partitioning strategies, reducing per-iteration compute overhead and demonstrating strong analytical thinking over real-world large-scale datasets.
View ProjectSkysail Full-Stack Air Travel Booking Platform
February 1, 2025 – April 1, 2025
Designed and deployed an end-to-end flight booking platform with RESTful APIs covering authentication, booking workflows, CRUD operations, and an admin reporting portal with structured data management views. Optimised PostgreSQL schema and query plans for high-concurrency access patterns, improving data retrieval performance and application reliability under simultaneous multi-user business operations. Implemented role-based access control and session management to support secure multi-user interactions, ensuring data integrity and consistent reporting accuracy across passenger and admin interfaces.
View ProjectPredictive Maintenance ML Pipeline for Robotic Systems
September 1, 2024 – November 1, 2024
Built an end-to-end supervised ML pipeline on sensor time-series data with anomaly detection to forecast robotic component failures at 95% accuracy, directly mirroring exception identification workflows central to business audit analytics. Designed modular feature engineering and model evaluation workflows with threshold-based alert logic, generating automated failure reports and visualisation dashboards interpretable by non-technical operations teams. Produced structured Excel-compatible analytical outputs summarising predicted failure risks and maintenance priorities, enabling data-driven scheduling and operational decision support across sensor domains.
View ProjectGoogle Cloud Data Analytics Certificate
Google Cloud Skills Boost
January 1, 2026 – Present
Associate Data Analyst
DataCamp
January 1, 2025 – Present
Data Science Bootcamp
Udemy
January 1, 2025 – Present
Full-Stack Web Development Bootcamp
Udemy
January 1, 2025 – Present
Intro to Cyber Security & Information Security Fundamentals
Infosys Springboard
January 1, 2024 – Present
Advanced Python and Java Programming
Harrison CADD
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning graph analytics, full-stack development, and predictive maintenance, indicates a broad interest in various technical domains. Their academic background in AI & Data Science, coupled with an internship in Biomedical AI & Backend Engineering, aligns well with the target role of an AI Engineer. The certifications in Data Analytics, Data Science, and Full-Stack Web Development further demonstrate a proactive approach to skill acquisition and a commitment to continuous learning. The involvement in hackathons and competitive summits suggests a drive for innovation and excellence, which are positive indicators for cultural fit in a dynamic technical environment.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving, and the ability to translate complex technical concepts into actionable insights, as seen in project descriptions. Their experience in building interactive dashboards and generating business-readable reports indicates good communication of technical results. The academic nature of projects suggests a structured approach to problem-solving and a capacity for independent research and development. However, direct evidence of teamwork, stress handling, or specific work attitude from the provided data is insufficient.