AI Engineer with less than a year in Generative AI & Data Analytics
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Aspiring Data Scientist | AI/ML Engineer | Data Analyst | Data Engineering with hands-on experience in machine learning, data analytics, business intelligence and Generative AI. Proficient in Python, Power BI, SQL and LLM APIs, with a proven ability to deliver data-driven insights and automated AI solutions that reduce manual effort and improve decision-making. Experienced in end-to-end ML pipelines from data preprocessing and EDA to model tuning and deployment-ready APIs with a strong focus on business impact and actionable analytics.
AIMIT - Deemed to be University
M.Sc. · Data Science
August 1, 2024 – June 30, 2026
St Aloysius College (Autonomous)
Bachelor of Computer Applications (BCA)
August 1, 2022 – June 30, 2024
IHub IT Solutions
AI/ML Intern
January 1, 2026 – April 1, 2026
Mangalore, Karnataka, India
Ethical Byte
Cybersecurity Intern
June 1, 2023 – July 1, 2023
Mangalore, Karnataka, India
AI-Powered Property Recommendation System
January 1, 2026 – April 1, 2026
Designed and integrated a RAG-based AI chatbot using Gemini, LangChain and Pinecone to provide context-aware property assistance and search. Developed AI-powered property advertisement generation using prompt engineering and Gemini LLM, reducing manual listing effort by ~60%. Implemented personalized property recommendations using semantic retrieval and vector search to improve recommendation relevance. Collaborated in an Agile team delivering production-ready AI features within sprint timelines.
Loan Approval Prediction, End-to-End ML System
July 1, 2025 – September 1, 2025
Built a modular, end-to-end binary classification pipeline to predict loan approval decisions across 614 real-world applicant records (13 features), automating credit screening for financial institutions. Benchmarked 4 ML algorithms (Logistic Regression, Decision Tree, Random Forest, XGBoost) using 5-fold stratified cross-validation; XGBoost achieved best performance at 83% accuracy and 0.84 ROC-AUC. Engineered features including log-transforms and EMI computation; handled missing values via median/mode imputation and applied StandardScaler improving model generalisation. Deployed an interactive Streamlit web app with real-time loan predictions and applicant feedback tips; containerized using Docker and hosted on Render.
Sales & Profitability Analytics Dashboard - Power BI
January 1, 2025 – February 1, 2025
Designed a 3-page interactive Power BI report (CEO & Managers, Marketing & Product Team, Order-Level Details) for Dataline Bike Company, replacing manual Excel/PDF reporting with real-time self-service analytics. Built a Profit by Country-Region world map, Revenue & Profit area chart (2017–2020) and Profit by Category bar chart revealing Bikes as the top profit driver at $11M out of $4.5M+ total profit across $43M+ in revenue. Engineered DAX measures for Revenue, Profit and Profit Margin % and built a Category/Subcategory matrix table enabling year-over-year (2017-2019) performance comparison across Bikes, Components, Accessories and Clothing. Added dynamic Category & Subcategory slicers for drill-down filtering, enabling stakeholders to self-serve insights without technical assistance and reducing ad-hoc reporting requests by an estimated ~80%.
Artificial Intelligence for All
Infosys Springboard
June 1, 2026 – Present
Basics of Python Programming
Infosys Springboard
June 1, 2026 – Present
Web Development
Internshala Trainings
June 1, 2026 – Present
Microsoft Power BI
Udemy
June 1, 2026 – Present
Probability and Statistics Using R
Infosys Springboard
June 1, 2026 – Present
Data Visualization Using Tableau
Infosys Springboard
June 1, 2026 – Present
Microsoft Excel
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from AI-powered recommendation systems to end-to-end ML pipelines and BI dashboards, indicates a broad interest and adaptability. The target role of 'AI Engineer' aligns well with their recent internship and project focus on Generative AI and ML. Their academic background in Data Science further strengthens this alignment. The volunteer and workshop facilitator roles suggest a proactive and collaborative mindset, which generally contributes positively to cultural fit.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as Communication, Teamwork, Leadership, Public Speaking, and Time Management. Project descriptions indicate collaboration in Agile teams and facilitating workshops, suggesting good operational fit for team-oriented environments. However, without specific assessment data on these skills, the depth of proficiency is inferred.