Professional Summary
Data Scientist with 3+ years of experience building machine-learning, large-language-model, and Generative-AI solutions in enterprise settings. Proven track record delivering RAG applications, agentic AI systems, and business-intelligence platforms across finance, supply chain, and technology — turning models into measurable business outcomes.
Technical Skills
Languages
Python, PySpark, SQL
AI / ML
Agentic AI, LLMs, RAG, Graph-RAG, AI-Native SDLC, Context & Loop Engineering, AI Solution Architecture, LangChain, LlamaIndex, Semantic Kernel, AutoGen
Cloud
Azure (AI Search, OpenAI, Functions), Google Cloud (BigQuery)
Visualization
Looker, Qlik Sense, Power BI
Databases
PostgreSQL, BigQuery
Dev Tools
Git, Azure Repos/Boards, Jira, FastAPI, Flask
Professional Experience
Industrial & Functional Decision Science Analyst 2022 – Present
Accenture Strategy & Consulting (Global Network)
★ Recent Highlights (2026)
SRE Agents
Autonomous AI agents that triage incidents, correlate logs & alerts, and suggest remediations.
MTTR ↓ 80%−35 hrs/wk toil
AI-Native SDLC
AI-assisted spec → code → review → docs workflow embedded into the delivery lifecycle.
80% faster delivery−60% review effort
CodeWiki Bot (Graph-RAG)
AI docs + chatbot over the codebase; auto-generates cross-repo dataflow & architecture diagrams.
12 repos12k+ docs−80% hunt time
Key Projects & Achievements
- Built a ServiceNow agentic bot (LlamaIndex + OpenAI) for automated IT-ticket resolution, cutting manual intervention 40%.
- Developed a RAG-based finance application with Azure AI Search and vector embeddings for contextual document querying.
- Created a synthetic-data generation pipeline using NVIDIA Nemotron-4 340B, producing 100,000+ privacy-preserving records at 95% statistical similarity.
- Implemented an automated code-converter tool transforming legacy
.scriptfiles to PySpark using Azure OpenAI + AutoGen. - Led cross-functional proof-of-value initiatives, presenting AI solutions to C-suite executives.
Additional Projects
- Supply-Chain NL2SQL: RAG chatbot on Azure Functions, reducing analyst query time 60%.
- B2B Lead Scoring: decision-tree classifier over 11M+ firmographic records, improving conversion 25%.
- Banking Capital Markets: Qlik Sense KPI dashboards for trading volume & market-liquidity analysis.
- HR Analytics Platform: 9 interactive Looker dashboards tracking attrition, hiring, and resource allocation.
Education
B.Tech, Civil Engineering
NIT Silchar · CGPA 8.1/10
NIT Silchar · CGPA 8.1/10
Higher Secondary
Board of Secondary Education, Assam · 86%
Board of Secondary Education, Assam · 86%
Certifications
Microsoft Azure AI Engineer Associate
Microsoft Azure Data Scientist Associate
Microsoft Azure Fundamentals
Machine Learning with Python (IBM)
RAG for Production (Activeloop)
LLMOps Applications (Udacity)
NVIDIA Deep Learning (neural networks & GPU)
Google Cloud Digital Leader
Key Competencies
ML Expertise
Supervised/unsupervised learning, model optimization, feature engineering
Deep Learning
Neural networks, transformers, modern AI architectures
Analytical Excellence
Complex data analysis into actionable insights