09/03/2026 updated
AM
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Data Scientist & Quantitative Modeler
Thrissur, India
Worldwide
B.Tech in Engineering Physics, Indian Institute of Technology (IIT) HyderabadAbout me
Data Scientist & IIT Hyderabad Engineering Physics graduate specializing in predictive modeling, quantitative analytics, and data visualization. I help businesses, financial entities, and research teams turn complex data into actionable strategic insights and production-ready models.
Machine Learning & Statistical Modeling
Expertise in applying machine learning algorithms including XGBoost, Random Forests, Neural Networks (CNN, RNN/LSTM), SHAP, Regression Analysis, and Hypothesis Testing to build end-to-end predictive pipelines and data-driven solutions.
Python & Data Science Frameworks
Proficiency in Python with key libraries such as NumPy, Pandas, SciPy, and Scikit-Learn, as well as PyTorch for deep learning, enabling scalable and efficient data processing and model development.
Modeling & Optimization
Strong background in Time Series Analysis, Signal Processing, Non-convex Optimization, and Computational Physics, applied to complex engineering and analytical problems including inverse design and physical modeling systems.
SQL & Database Management
Practical experience with SQL for querying relational databases, data extraction, and supporting end-to-end data science workflows.
Deep Learning & Neural Networks
Knowledge of neural network architectures, hyperparameter tuning, Convolutional Networks (CNNs), and Sequence Models, with certification from DeepLearning.AI.
Data Visualization & Storytelling
Ability to build interactive visualization modules and deliver actionable insights from high-frequency spatial and analytical data.
Signal Processing & Noise Reduction
Experience in building noise-mitigation and matched-filtering pipelines, spectral density estimation, and time-frequency analysis for anomaly detection in continuous time series.
Version Control & Linux/Bash
Familiarity with Git for version control and Linux/Bash for scripting and managing development environments.
Project Management (Agile & Scrum)
Certified in Google Project Management, with knowledge of project planning, risk assessment, Agile and Scrum methodologies, and cross-functional stakeholder communication.
Expertise in applying machine learning algorithms including XGBoost, Random Forests, Neural Networks (CNN, RNN/LSTM), SHAP, Regression Analysis, and Hypothesis Testing to build end-to-end predictive pipelines and data-driven solutions.
Python & Data Science Frameworks
Proficiency in Python with key libraries such as NumPy, Pandas, SciPy, and Scikit-Learn, as well as PyTorch for deep learning, enabling scalable and efficient data processing and model development.
Modeling & Optimization
Strong background in Time Series Analysis, Signal Processing, Non-convex Optimization, and Computational Physics, applied to complex engineering and analytical problems including inverse design and physical modeling systems.
SQL & Database Management
Practical experience with SQL for querying relational databases, data extraction, and supporting end-to-end data science workflows.
Deep Learning & Neural Networks
Knowledge of neural network architectures, hyperparameter tuning, Convolutional Networks (CNNs), and Sequence Models, with certification from DeepLearning.AI.
Data Visualization & Storytelling
Ability to build interactive visualization modules and deliver actionable insights from high-frequency spatial and analytical data.
Signal Processing & Noise Reduction
Experience in building noise-mitigation and matched-filtering pipelines, spectral density estimation, and time-frequency analysis for anomaly detection in continuous time series.
Version Control & Linux/Bash
Familiarity with Git for version control and Linux/Bash for scripting and managing development environments.
Project Management (Agile & Scrum)
Certified in Google Project Management, with knowledge of project planning, risk assessment, Agile and Scrum methodologies, and cross-functional stakeholder communication.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
EnglishNative speakerHindiGood
Project history
Developed an end-to-end shot-by-shot predictive model estimating point-win probability based on spatial court coordinates and trajectory dynamics. Applied XGBoost and SHAP value attribution to quantify shot impact and tactical decision efficiency. Built interactive visualization modules to deliver actionable tactical insights from high-frequency spatial tracking data.
Built noise-mitigation and matched-filtering pipelines to extract faint chirp signals from heavily corrupted sensor streams. Performed spectral density estimation and time-frequency analysis for anomaly detection in continuous time series.
Designed an automated optimization framework for inverse design of electromagnetic metamaterial structures. Accelerated spectral response simulation convergence by 40% using surrogate machine learning models.