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Data Science with less than a year in AI & Data Science with 0.0 Years in Machine Learning & Busines
MBA graduate specializing in Artificial Intelligence & Data Science (CGPA: 8.11, Graphic Era University) with a strong foundation across the full analytics spectrum — from raw data ingestion to machine learning, business intelligence, and executive-level reporting. Hands-on expertise in SQL, Python, Power BI, PySpark, ETL pipelines, and data warehousing, demonstrated through seven independently built end-to-end projects processing millions of records. Proven ability to translate complex datasets into actionable business insights and KPI-driven dashboards. Equally effective as a Data Analyst, Business Analyst, Power BI Analyst, Data Scientist, or MIS Analyst, bringing both technical depth and business communication skills to data-driven organisations.
Graphic Era (Deemed to be University)
MBA · Artificial Intelligence & Data Science
August 1, 2024 – June 30, 2026
D.A.V P.G. College
Bachelor of Commerce (B.Com) · Commerce
August 1, 2020 – June 30, 2023
Climate-Risk-Adjusted Loan Portfolios for Renewable Energy Infrastructure
January 1, 2026 – June 1, 2026
Evaluated infrastructure loan default risks across Indian states by merging 35 years of historical climate anomaly and natural disaster data with standard corporate banking metrics. Predicted non-performing assets (NPAs) using ensemble ML models, providing data-driven risk scoring for lending decisions in the renewable energy sector.
Multimodal Deepfake Detection Using Audio & Video Analysis
January 1, 2026 – June 1, 2026
Developed a dual-stream multimodal network fusing video frame spatial models (EfficientNet-B4) and audio spectrogram classifiers (ResNet-18) to isolate synthetic deepfakes. Incorporated SHAP and Grad-CAM explainability layers, demonstrating ability to build interpretable AI solutions — critical for business and compliance use cases.
End-to-End Sales Analytics Solution
January 1, 2025 – January 1, 2025
Designed and implemented a star schema data warehouse in SQL Server to support structured corporate BI and scalable historical KPI tracking across multiple business units. Automated high-performance ETL pipelines using SSIS to extract, clean, and consolidate multi-source operational sales data into a unified analytical layer. Analysed a 1.27M+ transaction record revenue dataset to identify key category performances, regional trends, and seasonal purchase variations — delivering management-ready insights. Built interactive Power BI dashboards monitoring operational logistics, tracking 830+ delayed shipments to uncover fulfilment bottlenecks and drive corrective action.
High-ROI Locations for Solar & EV Charging Infrastructure
January 1, 2025 – January 1, 2025
Engineered a dual-mode deployment pipeline mapping optimal intersections for solar and EV charging stations based on regional irradiance, traffic density, and CAGR of EV registrations. Deployed a 6-tab Streamlit decision-support application enabling business and policy stakeholders to explore location recommendations interactively.
The 'Digital Detective' Threat Intelligence Knowledge Graph
January 1, 2025 – January 1, 2025
Constructed a Threat Intelligence Knowledge Graph using GraphSAGE to map entity relationships and execute link prediction, proactively detecting cyber threat actors.
Energy Demand Forecasting Model
January 1, 2024 – January 1, 2024
Built a scalable time-series forecasting model for energy demand planning using PySpark on large-scale datasets, demonstrating big data analytics capability. Reduced forecast error by 15% using Random Forest Regression vs. baseline models, achieving R² = 0.989 and RMSE = 1.01 — production-level accuracy for business planning. Engineered features and pre-processed time-series signals, improving model robustness through noise reduction and temporal feature extraction.
Threat & Distress Detection System
January 1, 2024 – January 1, 2024
Pre-processed and tokenised 211K+ unstructured textual records; engineered TF-IDF text representations optimised for NLP classification architectures. Trained a Logistic Regression classifier achieving 75.84% accuracy and 72.27% recall on a multi-class threat detection task using imbalanced real-world data.
Design Thinking - A Primer
NPTEL (IIT Madras)
June 1, 2026 – Present
SQL Database Management Training
Accelerant Software Solutions
June 1, 2026 – Present
GenAI-Powered Data Analytics Job Simulation
Tata (Forage)
June 1, 2026 – Present
Data Analytics Job Simulation
Deloitte (Forage)
June 1, 2026 – Present
Introduction to Prompt Engineering
Simplilearn
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse range of applications for data science, from finance (climate-risk), to cybersecurity (threat intelligence), to energy (demand forecasting, infrastructure planning), and sales analytics. This breadth of interest and application aligns well with a dynamic, innovation-driven culture. The focus on interpretable AI and business-ready insights in projects also suggests a practical, value-oriented mindset. However, the lack of professional experience and the psychometric test results raise questions about their readiness for a senior role's collaborative and high-pressure environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and a structured approach to data science challenges. The 'Design Thinking' certification further supports a methodical approach to problem-solving. The English test score of 54/100 suggests potential areas for improvement in communication clarity and professional language usage, which are critical for operational fit in a senior role. The psychometric test score of 240/500 indicates potential concerns regarding logical reasoning, work attitude, stress handling, and team collaboration, which are vital for senior-level operational effectiveness.