Aishwarya Nair

AI Product Manager with prior experience in automation and digital transformation within the banking and financial services sector, now transitioning into AI-driven product leadership. Currently pursuing a Master’s in Artificial Intelligence and Innovation at the National University of Singapore (NUS), with hands-on exposure to machine learning, GenAI, and data-driven product development. Brings a strong blend of domain knowledge in banking automation, product thinking, and AI innovation to build intelligent products that deliver measurable business impact.

• mRNA classification (machine learning and deep learning, group project with 4 members). Built and benchmarked ML and deep learning models for biological sequence classification, achieving approximately 82% accuracy, approximately 0.83 F1 score, approximately 90% recall, and ROC-AUC approximately 0.89 using optimized k-mer feature engineering, and demonstrated that interpretable models (random forest) can match deep learning performance with lower deployment complexity.

Tech stack: Python, Scikit-learn, TensorFlow/Keras, NumPy, Pandas, Git.

Repository link: https://github.com/KalyaniVijayPakhale/MSI5001-Group-Project

• Built and positioned agentic AI solutions with human-in-the-loop governance for enterprise workflows, applied Lean Canvas, Hurdle Model, and value-driven business strategy to AI product design, and developed AI product business plans covering market analysis, GTM, operations, and financial projections
• Applied innovation and AI methodologies to design, validate, and position new venture concepts; experienced in design thinking, lean startup experimentation, business modeling, and AI-assisted research; strong in customer discovery, MVP prototyping, market sizing, and executive-level communication