About
A highly analytical and results-driven Data Scientist with a strong foundation in Machine Learning, Financial Engineering, and advanced statistical modeling. Proven ability to develop and deploy production-ready AI/ML solutions, optimize trading strategies, and extract actionable insights from large datasets to drive significant business and financial outcomes. Eager to leverage expertise in quantitative research and data science to contribute to innovative projects in dynamic environments.
Work
udaan.com
|Analyst - Data Science Intern
Bangalore, Karnataka, India
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Summary
Led data science initiatives at udaan.com, developing advanced AI/ML models and performing rigorous data analysis to optimize business processes and enhance decision-making.
Highlights
Engineered a production-ready NL2SQL model leveraging graph-based CTE retrieval, RAG, and parallel multi-run generation, optimizing for minimal token usage and robust, hallucination-resistant deployment.
Developed a Deep Q-Network to dynamically optimize inventory item discounts based on expiry, balancing maximum revenue generation with minimum wastage.
Conducted A/B and time-series analysis with paired t-tests to evaluate CPOD rollout impact on AUM, providing statistical and practical insights into business performance.
Constructed and maintained Retention Matrices using Spark SQL for datasets up to 3 billion rows, automating Supply Chain Cost calculations and visualizing results with Excel and Power BI.
Quant Insider
|Quantitative Researcher, Part-time
Remote, Virtual, India
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Summary
Developed and backtested algorithmic trading strategies, contributing to advanced study materials and improving client confidence in technical interviews.
Highlights
Developed and backtested algorithmic trading simulations and strategies, providing practical case studies for training purposes.
Researched and documented cutting-edge quant finance strategies, translating complex findings into advanced study materials.
Contributed to significant improvements in client confidence for technical interviews through specialized content.
Soul AI
|RHLF, LLM, Data Scraping
Remote, Virtual, India
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Summary
Contributed as a domain expert to state-of-the-art Large Language Model (LLM) training and development, focusing on Reinforcement Learning via Human Feedback.
Highlights
Acted as a domain expert in Reinforcement Learning from Human Feedback (RLHF), contributing to the training and fine-tuning of state-of-the-art Large Language Models (LLMs).
Collaborated with a cross-functional team of 50+ members to develop a cutting-edge AI model, leveraging expertise in Probability and Statistics.
Enhanced the overall effectiveness of AI solutions by contributing to over 500 prompts, ensuring robust model performance.
Education
Delhi Technological University
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Bachelor of Technology
Mathematics and Computing Engineering
Grade: CGPA: 8.4
Courses
Machine Learning
Probability and Statistics
Financial Engineering
Stochastic Processes
Stochastic Calculus
Regression Analysis
Linear Algebra
Data Structures and Algorithms
Operating Systems
DBMS
Languages
English
Skills
Programming Languages
C++, Python, R, SQL, MATLAB.
Frameworks
PyTorch, PySpark, Langchain, Pandas, NumPy, Scikit-learn, Statsmodels, Seaborn, Matplotlib.
Tools & Technologies
MS Excel, Power BI, Databricks, Git/GitHub.
Data Structures & Algorithms
LeetCode, GFG, Data Structures, Algorithms.
Quant Finance
Algorithmic Trading, Portfolio Optimization (Markowitz model and CAPM), Options Pricing (Binomial Model, CRR model, Black-Scholes).
Machine Learning
Neural Networks, Deep Reinforcement Learning, LSTM, CNN, XGBoost.