May 2022 – Jul 2025 · 3 yrs 2 mos

• Key Responsibilities
• Lead the Automation COE, driving AI/ML and GenAI adoption across enterprise functions, including investment banking and BFSI.
• Architected AI solutions for financial document summarization using Python, RAG, Graph RAG, and Vector DBs (Pinecone, FAISS), reducing manual analysis time by 40%.
• Developed LSTM-based stock price prediction models (64% accuracy) and integrated insights into algorithmic trading strategies.
• Designed customer churn prediction and recommendation systems (Random Forest, Gradient Boosting), achieving 15% lower churn and 20% higher engagement ROI.
• Optimized credit risk and fraud detection models (logistic regression, anomaly detection), saving $2M annually.
• Leadership & Impact
• Mentor 10+ data scientists on GenAI tools (LangChain, Hugging Face) and MLOps best practices.
• Built Power BI dashboards to track model KPIs (precision, recall, ROI) for continuous improvement.
• Reduced operational costs by 30% via automation and selective data retrieval.
• Technologies: Python, TensorFlow, PyTorch, AWS SageMaker, NLP, LLMs (LLAMA), Vector DBs, Spark, Hive.

May 2020 – May 2022 · 2 yrs

• Key Responsibilities
• Led AI/ML projects for investment banking, including financial document summarization (RAG, Vector DBs) and sentiment analysis for trading strategies.
• Developed predictive models (LSTM, XGBoost) for stock prices and customer churn, improving accuracy by 10%+.
• Automated credit risk assessments using logistic regression and feature engineering, reducing defaults by 7%.
• Collaborated with traders to deploy models into production, enhancing decision-making speed.
• Leadership
• Mentored junior data scientists and streamlined workflows using MLFlow and Docker.
• Created Power BI dashboards to monitor model performance and business impact.
• Technologies: Python, SQL, Scikit-learn, Spark, AWS, Power BI.

Sep 2018 – May 2020 · 1 yr 8 mos

• Key Responsibilities
• Built ML models for fraud detection (AUC: 0.85) and credit risk (AUC: 0.90) using Python and Scikit-learn.
• Automated data pipelines (PySpark, Hive) to reduce processing time by 25%.
• Supported customer churn projects with feature engineering and Random Forest models.
• Developed Power BI reports to visualize model outputs for stakeholders.
• Achievements
• Contributed to a 15% reduction in churn rates via personalized recommendation systems.
• Earned 2 Macquarie Awards for data optimization initiatives.
• Technologies: Python, SQL, SAS, Spark, Excel.

Sep 2016 – Sep 2018 · 2 yrs · Gurgaon, India

Dec 2015 – Sep 2016 · 9 mos · Noida Area, India

Dec 2012 – Dec 2015 · 3 yrs · Noida Area, India · On-site

• Worked on end to end test automation for Algo-Trading tools like Autoheadger, Trade Prematcher and Virtual Market Order (Order Agrregator). Migrated all test automation over AWS.
• Also worked on multiple D2D and D2C Fixed Income Trading Market Gateways like MarktAxe, BloomBerg, eSpeed, Getco, ISwap, BrokerTec and DealerWeb and automated all test flows following BDD/TDD Methodlogies.

Apr 2010 – Dec 2012 · 2 yrs 8 mos · Noida, Uttar Pradesh, India

• Software Engineer at HCL Technologies.