• 💬 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

Completed Certifications

• ✅ IBM Data Science Professional Certificate — IBM / Coursera
• ✅ Data Science Fundamentals with Python and SQL — IBM / Coursera
• ✅ 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 Modelling Using Machine Learning — End-to-end ML pipeline on the German Credit Dataset using an Extra Trees model (ROC-AUC 0.78–0.82), with a Streamlit app for real-time default prediction
• Insurance Claims Prediction & Risk Analytics — XGBoost model trained on 58,592 policyholder records to score claim likelihood, deployed as a Streamlit app for underwriter risk decisions
• Walmart Data Analysis: End-to-End SQL + Python — End-to-end pipeline on Walmart sales data: Python cleaning and feature engineering, loading into MySQL and PostgreSQL, and SQL analysis of revenue, profitability, and customer behavior

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

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