Kshitij S.

Machine Learning Engineer specializing in quantitative finance with proven track record in algorithmic trading systems and financial forecasting. Ranked #1 out of 18,166 professional data scientists in a time series forecasting Kaggle competition. Former VP at Citi Bank with 7+ years building production ML systems. Most of all, I adore logical problem solving! I'm also a former competitive chess player (rated 2073 ECF) . Available for: ML model deployment, data pipeline architecture, Strategy development, backtesting systems, quantitative research, financial dashboards, data analytics. Core Expertise 📊 Quantitative Finance & Trading End-to-end algo trading pipelines: Strategy development → Backtesting → Live deployment Trading platforms: Interactive Brokers API, TradingView, QuantConnect, MetaTrader (MQL4/5), cTrader Risk modeling: Options pricing (Black-Scholes, Monte Carlo), volatility modeling (GVAR, GARCH) Market data engineering: Massive (Polygon) AWS S3, real-time feeds, historical data pipelines 🤖 Machine Learning & AI Time series forecasting: ARIMA, LSTM, GRU for financial markets ML algorithms: XGBoost, LightGBM, Random Forests, Neural Networks Deep learning: CNNs for pattern recognition, RNNs for sequence prediction Natural Language Processing: Sequence-to-Sequence Encoder-Decoder Transformer Models with Attention Feature engineering: Target encodings, geospatial analysis, text vectorization 💻 Technical Implementation Languages: Python, Scala, SQL, R, C++, Java, Spark ML/DL frameworks: PyTorch, TensorFlow, scikit-learn, JAX Data engineering: PostgreSQL, AWS S3, REST APIs, real-time streaming Deployment: FastAPI, Flask, Streamlit dashboards, Docker Notable Achievements Kaggle Competition Winner: 1st place (out of 18,166) in 1C Future Sales Prediction Live Trading Success: Deployed strategy which achieved 25% CAGR at a prop trading firm for 3 years Enterprise Scale: Built forecasting models for 60+ countries at Citi Bank Academic Excellence: MS Computer Science (ML) Georgia Tech (GPA 3.9), MS Quantitative Finance (GPA 3.7) Certifications: CFA Level 2, FRM Level 1 Recent Projects 1. Building Custome Backtesting Engine in Python, Strategies & Indicators in MT5, MQL, NT8 2. Volatility clustering using Dynamic Time Warping for casino game crash prediction 3. Options chain visualization & credit spread calculator with Polygon data feeds 4. Yield curve forecasting model (PCA-based) outperforming legacy systems 5. Neural machine translation using Transformers with attention mechanisms How I Work I focus on delivering robust, scalable solutions that solve real business problems. Whether you need a complete trading system, risk model optimization, or ML-powered financial analysis, I bring both academic rigor and practical experience to ensure successful outcomes. I am especially passionate about data engineering - building robust, scalable and efficient data architectures.