Headline

Data Scientist in KPMG| Data Engineer at Oracle | Data Science, Claude Code, MCP, LLMs, RAGs, PL/SQL, Python | 4 Years of Experience | Computer Science Gold Medalist

About

Interests: GenAI, RAG architectures, ML systems, cloud analytics Open to: ML/Data roles, GenAI projects, Technical consulting discussions More about me : I’m a Machine Learning and Data Engineer with 3.5+ years of experience building scalable data platforms, ML pipelines, and GenAI-powered applications in enterprise and consulting environments. Currently at Oracle (Staff Consultant), I design and deliver end-to-end AI and analytics solutions—from ETL/ELT pipelines and cloud data warehouses to LLM-based semantic search, anomaly detection, and forecasting systems. My work has improved analyst productivity by 35–40%, reduced data load times by up to 40%, and enhanced early risk detection accuracy by 15–25%. What I specialize in • Machine Learning & Data Science (Python, scikit-learn, TensorFlow, PyTorch) • GenAI & LLM systems (RAG, embeddings, vector search, LangChain) • Data Engineering & Analytics (ETL/ELT, ODI, PySpark) • Cloud Platforms (Oracle Cloud Infrastructure, Azure ML) I started my journey as a Computer Science Gold Medalist (GPA 9.68) and have since worked at the intersection of data engineering, distributed systems, and applied AI—delivering production-grade solutions across finance, healthcare, and enterprise analytics. Beyond the tech, I’m known for clear communication, stakeholder collaboration, and solution-oriented thinking. I enjoy translating complex technical problems into scalable, business-ready systems.

Location

India

AI stack

claude

hugging face

langchain

langgraph

langsmith

claudecode

Work experience

Senior Data Scientist at KPMG, May 2026 - Present · 5 mos

Staff Consultant ( Data Engineering) at Oracle, Sep 2024 - Apr 2026 · 1 y 7 mo, India, 1. Led last-minute ETL workaround design during object storage failure in the newly launched OCI Madrid region, ensuring zero data pipeline downtime. 2. Developed SELECT AI Python modules for GenAI-assisted SQL/query generation, improving analyst productivity by 35–40% in internal testing. 3. Designed and implemented end-to-end AI/ML proof-of-concepts (anomaly detection, time-series forecasting) for healthcare use cases, achieving 15–25% improvement in early risk detection accuracy over baseline statistical models. 4. Built GenAI-based interview assessment and resume screening POCs, leveraging LLMs for automated evaluation and insights. 5. Designed drill-down, hierarchical Oracle Analytics Cloud (OAC) dashboards for General Ledger analytics, reducing ad-hoc reporting requests by ~30% and enabling executive-level insights. 6. Executed and optimized SQL, Python, and PL/SQL code for large-scale analytics workloads. 7. Performed ETL performance tuning by optimizing SQL, enabling parallel execution, reducing data volumes, and refining ODI Knowledge Modules, resulting in 25–40% reduction in load times. Actively working with Select AI, GenAI services, OAC, ODI, and OAS to build scalable data and AI solutions.

Associate Consultant ( Data Engineering ) at Oracle, Aug 2022 - Sep 2024 · 2 y 1 mo, India, 1. Built a production-grade AI/ML Q&A solution using Large Language Models on OCI Data Science, enabling semantic search across enterprise documents. 2. Developed an LLM-based enterprise Q&A system using OpenAI APIs, embeddings, and vector search, reducing information retrieval time by ~50%. 3. Implemented Sentiment Analysis POC using OCI and Oracle Analytics Cloud, achieving ~98% accuracy for audio-based inputs. 4. Designed and maintained data and AI platforms supporting finance and enterprise analytics workloads. 5. Worked extensively with structured (relational) and unstructured data (documents, transcripts) to support end-to-end AI workflows. 6. Designed ETL and feature engineering pipelines feeding downstream LLM applications, improving data freshness and reliability by ~25%. 7. Built semantic search pipelines using vector databases and similarity scoring techniques. 8. Implemented BICC → ADW data pipelines, extracting Fusion data into a centralized Data Lake using BICC, OTBI, ODI, and ADW. 9. Created a centralized enterprise repository for Finance, SCM, and HCM (Fusion & EBS) by consolidating multiple ODI work repositories into a unified GSC repository. 10. Designed and implemented OAC reports and dashboards, supporting business-critical analytics use cases. 11. Collaborated closely with business stakeholders and data teams, reducing analysis turnaround time by ~25%.

Internship in Data Science, Machine Learning, and AI using Python at Indian Institute of Technology, Ropar, Sep 2021 - Oct 2021 · 2 mos, • Analyzed 10,000+ records to identify pricing trends and behavioral patterns using statistical analysis and machine learning. • Built and evaluated a Random Forest Regressor achieving 85–90% accuracy, demonstrating strong problem-solving and model validation skills. • Delivered an end-to-end ML solution from data ingestion to Flask-based deployment, simulating a pro- duction data science environment.

Education

Bachelor of Technology Honors, Computer Science and Engineering, Heritage Institute of Technology

Carmel High School