Aarthi Ashokan is a Senior Data Scientist with three years of focused experience building predictive models, feature engineering pipelines, and production-ready analytics in Python. She has applied advanced statistical techniques across finance and payments domains, most recently at JPMorgan Chase following work at Fiserv where she led macroeconomic forecasting, synthetic data generation, fraud analytics, and LLM-driven reporting. Her background blends academic research in experimental characterization and mathematical modeling from IIT Madras with practical test-engineering and performance profiling experience from Infosys, giving her a strong foundation in both experimental design and production stability. Comfortable with scikit-learn, numpy, pandas and end-to-end deployment, she bridges rigorous statistical thinking with pragmatic engineering. Based in Secaucus, NJ, she combines a systems-engineering MS from Rutgers with a chemical engineering bachelor’s, a mix that informs her methodical approach to complex data problems. Colleagues value her ability to translate deep research instincts into scalable, business-facing ML solutions.
3 years of coding experience
6 years of employment as a software developer
Bachelor's degree, Chemical Engineering, 8.93, Bachelor's degree, Chemical Engineering, 8.93 at St. Joseph's College Of Engineering
Master of Science - MS, Industrial and Systems Engineering, Master of Science - MS, Industrial and Systems Engineering at Rutgers University
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