Haritha Selvakumaran

About Haritha Selvakumaran

Hey there! I am a graduate student at Northeastern University, Boston, MA pursuing a Master of Science in Computer Science with a concentration in Artificial Intelligence and Data Science. I have an undergraduate degree in Electronics and Telecommunication, where I had exposure to subjects like Machine Learning and Artificial Intelligence, which led to my passion for data. I have interned as a Data Science Intern, where I created and deployed machine learning models to production using transfer learning and performed analytics for a business-use case. I have also worked as a Deep learning Intern where my work focused on researching various deep learning models and deploying them. The model I created was deployed as one of the important feature of the company\'s app and have increased the accuracy of the existing model by a significant amount. This internship has taught me client-facing collaboration and critical thinking. Following is an overview of my technical skills -Languages - Python, R, C++, C, Java, HTML, Packages - Tensorflow, Keras, OpenCV, NLTK, SciPy, Scikit-learn, Pandas, Numpy, MatplotlibConcepts - Machine Learning Algorithms, Deep Learning Algorithms, CNNs, GANs, Data Structures andAlgorithmDatabases - MySQL, PostgreSQL, BigQuery, MongoDBVisualization Tool - Tableau, Power BIBeyond my technical competencies, I possess strong analytical and problem-solving capabilities. I derive genuine satisfaction from unraveling intricate problems, discerning underlying patterns, and devising creative solutions. Throughout my academic journey, I have undertaken diverse projects that have required me to navigate complex datasets, meticulously clean and preprocess data, and apply tailored algorithms to unearth invaluable insights.

Experience

1. Quantitative Analytics Associate

   JPMorganChase

   Feb 2025 — Present · NY, US

   Working in Model Risk Governance & Review (MRGR ) Business Banking and Wealth Management team, building internal validation tools and reviewing statistical and machine learning models across forecasting, underwriting, and risk use cases.Building Autotester, an LLM-enabled time series validation framework that supports exploratory analysis, stationarity testing, model training, forecasting, and diagnostic evaluation through interactive user-driven workflows.Developing Databricks-linked workflows that connect inputs, notebooks, cluster execution, and output storage to support scalable review and testing processes.Reviewing forecasting, valuation, and business decision models (including time series, XGBoost, Fair Lending, and underwriting), assessing model methodology, variable selection, parameterization, and underlying assumptions.Supporting model governance processes including OPM configuration, validation setup, and MISIX lifecycle management across multiple models

Education

• Northeastern University

  Master of Science - MS, Computer Science

• Savitribai Phule Pune University

  Bachelor of Engineering - BE, Electronics and Telecommunications Engineering