Data Science & Quant-Finance • Robust Large Scale Data Pipelines on AWS/Azure • GenAI Tooling • Trading Backtesting/Realtime Systems • Derivatives

Data professional with 2 years of hands-on experience in financial data engineering & analytics. I design scalable ingestion & transformation pipelines (historical + real‑time), optimize quantitative research backtesting fidelity, and build lean automation + GenAI tooling that turns raw market data into actionable strategy insights.

• Data Collection & Engineering – Large-scale real-time data collection, cleaning, processing, transformation, and storage/caching on cloud services (experience capturing real-time options snapshot data at 0.013s latency); building scalable & robust web crawlers/scrapers (dynamic sites; BrightData clients + personal experiments); market/options data engineering (high-volume ingestion, normalization, replay).
• MLOps & Analytics – Designing & deploying end-to-end MLOps pipelines using MLflow, Databricks, DVC, etc., focusing on levels 0–2 from the Google Cloud Practitioners Guide to MLOps; predictive analytics model development using NLP/ML with optimization.
• GenAI & Automation – GenAI augmentation for LLM-assisted artifact generation, prompt tooling, DSPy / LangChain; automation of pipelines & cloud operations with high reliability.
• Backtesting & Research Enablement – Backtesting architecture ensuring simulation fidelity, performance profiling, reproducibility; quant research enablement via research tooling, rapid prototyping, CI/CD hardening.
• Cloud & Infrastructure Automation – Complete cloud automation with 99.99% bug-free code, leveraging AWS EC2/S3/IAM/CloudWatch wrappers.

ZfenseLabs Inc — Data Scientist (Finance) (Contract) (Remote, Jun 2024 – Sept 2025)

• Re-architected core options & equities backtesting components improving simulation fidelity + maintainability.
• Built concurrent historical + live options data pipelines (Alpaca REST, Databento RTC) on lean EC2 footprints.
• Developed GenAI research tooling (DSPy, LiteLLM, Bedrock, LangChain) for strategy prototyping & artifact automation.
• Authored reusable AWS automation wrappers (S3, EC2, CloudWatch) for monitoring & resilient session recovery.
• Instituted CI/CD, test harnesses, and performance profiling across analytics stack.

SRIJAN — Project Executive MIS / IT (New Delhi, Jul 2021 – Feb 2022)

• Produced modular MIS components; automated validation + multi-program reporting.
• Managed relational data assets & real-time dashboards (Google Data Studio) for stakeholders.
• Led trainings and maintained organizational web assets.

Program	Institution	Period
BS, Data Science & Applications	IIT Madras	2025–Present [ONLINE]
PGD, Statistical Methods & Analytics	Indian Statistical Institute	2023–24
MDP, Project Management for Rural Livelihoods	IRMA	2021
PGDM, Development Management	DMI	2018–20
B.Tech, Computer Science & Engineering	Gauhati University – Dept of IT	2012–16

• Data Science Math Skills by Duke University
• India Data Portal Workshop — ISB, Bharti Institute of Public Policy
• Virtual Training on T4D: Digital Data Collection for M&E — FICCI Aditya Birla CSR Centre

Articles (OpenGenus IQ):

• Pandas DataFrame (Complete Guide)
• Concept of Multiple Instance Learning

• Experimenting with the traditional Black-Scholes Model (BSM) until it breaks
• Researching optimization techniques for Non-Integer Programming (NIP)
• Practicing advanced data structures in C

Open to: Any freelance contracts or projects related to data domains. If you have offers you’d like to bid on, I can help get your task done with very high quality.

Feel free to reach out via any of the listed emails for collaboration or opportunities.

_{*Reflects most recent update (auto-sync not enabled). Last updated: Sep 2025.}