• 💬 Ask me about Data Science, Python, SQL, Machine Learning, Quantitative Trading, Risk Management

• 📫 How to reach me theanshulworld@gmail.com

• ⚡ Fun fact I managed funded trading accounts while building ML models—talk about managing multiple risk portfolios!

• 🎓 Currently pursuing MBA in Analytics & Data Science at Manipal University Jaipur

Data Scientist & Proprietary Trader building predictive models and risk systems at the intersection of quantitative strategy and production analytics. Currently pursuing an MBA in Analytics & Data Science at Manipal University Jaipur while actively managing funded trading accounts.

My unconventional path from Proprietary Trading → Data Science has shaped how I approach problems: extract signal from noise, manage risk under uncertainty, and execute with discipline. Every trading decision grounds in real-time market analysis and pattern recognition—skills that directly transfer to building robust ML pipelines and financial risk models.

Core Competencies:

• Quantitative Analysis & Risk Management: Portfolio optimization, drawdown analysis, statistical backtesting, financial metrics tracking
• Predictive Modeling: Classification models (credit risk, churn prediction), ensemble methods, feature engineering, model validation
• Data Engineering: SQL procedures (PL/pgSQL), normalized database architecture, ETL design, data pipeline automation
• Analytics & Visualization: Power BI, Tableau, Python data stacks (Pandas, NumPy), dashboard design for stakeholder decisions
• Programming: Python (Scikit-learn, TensorFlow, Streamlit), SQL (PostgreSQL, MySQL, Oracle), Excel/VBA
• Financial Acumen: Market microstructure, technical analysis, risk-adjusted returns, capital preservation frameworks

Recent Work:

• Built and deployed credit risk classification models using Scikit-learn (Streamlit-based production systems)
• Designed normalized SQL databases with automated procedures for healthcare claim processing (Aetna via Concentrix)
• Created Tableau dashboards for forensic data analysis (Deloitte simulation)
• Manage multi-asset portfolios across forex/financial markets with rigorous performance tracking and optimization

Target: Full-time Data Scientist / Analytics Engineer roles in BFSI, fintech, and enterprise analytics where quantitative rigor and technical execution drive business impact.

Programming Languages

Data Science & Machine Learning

Data Visualization & Analytics

Databases & Data Platforms

Big Data & Distributed Computing

Cloud Platforms

Version Control & DevOps

Development Tools

Predictive Models & Risk Systems

• Classification models (credit risk, behavioral prediction) with rigorous train/test validation
• Backtesting frameworks for trading strategies with statistical significance testing
• Feature engineering pipelines for high-dimensional financial and operational datasets

Data Infrastructure

• SQL-driven data warehouses with normalized schemas and automated ETL procedures
• Python-based data pipelines (Pandas, NumPy) for claim processing, market data ingestion, and analysis
• Production ML systems deployed via Streamlit for real-time scoring and monitoring

Analytics & Dashboards

• Executive dashboards in Power BI / Tableau translating raw data into decision-ready insights
• Performance tracking systems for portfolio optimization and behavioral pattern identification
• Forensic data analysis frameworks for anomaly detection and root-cause investigation

Decision Science

• Statistical hypothesis testing and A/B experimentation frameworks
• Risk-adjusted performance metrics and capital allocation optimization
• Quantitative strategy development with consistent, disciplined execution under market volatility

Currently Pursuing

• 🔄 IBM Data Science Professional Certificate — In Progress (Coursera)

Completed Certifications

• ✅ IBM Data Analyst Professional Certificate — IBM / Coursera
• ✅ IBM AI Foundations for Business — IBM / Coursera
• ✅ SQL Basics for Data Science Specialization — UC Davis / Coursera
• ✅ Python for Everybody Specialization — University of Michigan / Coursera
• ✅ Microsoft Business Analyst Certificate — Microsoft / Coursera
• ✅ Google AI Essentials — Google / Coursera
• ✅ Google AI Professional Certificate — Google / Coursera

• Credit Risk Classification Model — End-to-end ML pipeline (Scikit-learn, Streamlit) predicting loan default probability with feature importance analysis
• Healthcare Claims Database — Normalized SQL architecture with automated PL/pgSQL procedures for Aetna claim processing and SLA tracking
• Quantitative Trading Dashboard — Real-time performance tracking system for multi-asset portfolio with drawdown analysis and risk metrics
• Tableau Forensic Analysis — Data forensics dashboard for anomaly detection and business conclusions (Deloitte simulation)

See repositories below for implementations, notebooks, and case studies.

Currently open to: Data Scientist, Analytics Engineer, and Quant roles in BFSI / fintech / enterprise analytics