Nityam Churamani

AI Researcher

Bengaluru, Karnataka, India5 yrs 1 mo experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in developing AI-driven multi-agent systems.
Proven track record in financial risk modeling.
Published research in cancer therapy and stock forecasting.

Stackforce AI infers this person is a Fintech expert specializing in AI and machine learning applications.

Contact

Skills

Core Skills

Machine LearningNatural Language Processing (nlp)Natural Language Processing

Other Skills

AI AgentsAlgorithm DevelopmentAlgorithmsApache SparkArtificial Intelligence (AI)Artificial Neural NetworksAutoGenAutoencodersAutomationBERT (Language Model)Big DataCloud ComputingData AnalysisData ScienceData Structures

About

I’m a Data Scientist & Applied AI/ML Analyst at JPMorgan Chase & Co., where I build intelligent systems at the intersection of Machine Learning, Natural Language Processing, and Financial Risk Modeling to solve high-impact problems in the real world. At JPMorgan, I work on developing multi-agent AI systems and fraud detection algorithms that leverage Large Language Models (LLMs), BERT embeddings, and frameworks like LangGraph, LangChain, and AutoGen. My work spans agentic AI systems that emulate crisis-time decision-making and ML pipelines that enhance compliance and trading surveillance for $400M+ in assets. My journey into AI began at PES University, where I earned the MRD scholarship twice and led data science initiatives at C.O.D.S. These academic experiences, along with two peer-reviewed IEEE publications in cancer therapy prediction and stock price forecasting, laid a strong foundation for my current work in applied AI. I’m passionate about combining domain knowledge with statistical rigor to develop interpretable, scalable, and ethical machine learning solutions—especially across finance. At JPMorgan, I’ve found a collaborative and forward-thinking environment that encourages pushing the boundaries of what’s possible with data.

Experience

5 yrs 1 mo

Total Experience

2 yrs

Average Tenure

2 yrs 10 mos

Current Experience

Jpmorgan chase & co.

2 roles

Applied AI ML Analyst

Promoted

Jun 2023 – Present · 2 yrs 10 mos · Hybrid

Project: Agentic Resiliency Management
Developed an AI-driven multi-agent system using LangGraph, LangChain, and AutoGen to simulate and validate 3,000+ recovery strategies for critical assets (staﬀ, sites, applications), ensuring operational continuity during crises.
Reduced manual risk analysis by 70% across 5 lines of business through intelligent agents that emulate crisis-time decision-making, strengthening resiliency for 300K+ assets and mitigating potential multi-million-dollar loss.
Accelerated recovery strategy analysis by 40% via autonomous validation and state tracking within the Agentic AI setup, boosting simulation throughput and reliability.
Project: Mapping Unmapped Staﬀ to Business Resiliency Plans
Evaluated machine learning and deep learning models, including autoencoders, artificial neural networks, and XG-Boost, to address the staﬀ-to-resiliency-plan mapping problem.
Developed an OpenAI-embedding-based similarity search method providing top-3 recommendations, achieving 96%+ mapping accuracy in validation.
Enhanced scalability by deploying automated mapping workflows, cutting labor costs by 60% while improving resiliency testing consistency.
Project: AI-Driven Trade Surveillance
Engineered supervised ML pipelines (XGBoost, Logistic Regression) to identify spoofing patterns across 10M+ transactions, improving fraud detection accuracy across $600M+ in Fixed Income, Swaps, Commodities, and FX assets.
Conducted validation of 300+ financial risk features for mathematical and logical integrity, enhancing reliability in predictive models.
Designed and deployed the Investigator Score, a quantitative risk metric, increasing alert capture precision by 30% and aiding decisions for 100+ compliance oﬃcers.
Applied NLP techniques (TF-IDF) on 4,000+ investigator comments to uncover 5 manipulation indicators(Time,
Volatility, Volume, Price and Momentum), reducing manual alert verification by 30%.

LangGraphLangChainAutoGenMachine LearningNatural Language Processing (NLP)XGBoost+1

Applied AI ML

Feb 2023 – May 2023 · 3 mos · Hybrid

Project: AI-Driven Trade Surveillance
Selected among 600+ students nationwide for the Applied AI/ML Trade Surveillance team managing $400M+ in Fixed Income assets.
Researched & validated 50+ financial risk features, improving model precision by 25% and reducing false alerts by 20%.
Collaborated with 5 cross-functional teams to operationalize AI-based fraud detection, enhancing risk identification speed by 20%.

Machine LearningFinancial Risk Modeling

Pesu venture labs

2 roles

Product Builder

Jun 2022 – Sep 2022 · 3 mos

Worked with clients and helped them solve their problems through tech.
Highlights:
Helped clients obtain better results through Natural Language Processing and novel Algorithms.
Automated the process of testing.

Natural Language ProcessingAlgorithms