Mohammad Faiz Ansari

Mohammad Faiz is a data scientist based in Mumbai who works at the practical end of machine learning. Their projects run from sentiment analysis on Amazon Alexa reviews to a heart disease risk model, and they have shipped a full AI customer support platform with role-based access control, RESTful APIs, and dashboards. They are comfortable across the stack, pairing Python and Scikit-learn with FastAPI, React, and PostgreSQL when a model needs to become something people actually use.

Their path has been hands-on and varied. At NetTech India they built models to sort incoming website leads using Logistic Regression, Random Forest, XGBoost, and NLP, while also counselling prospective students on which IT training programs fit their goals. Before that, a year on the Rapido marketing team sharpened their sales instincts, where they hit a 90% conversion rate and kept sales data in Advanced Excel. Earlier still, at Globalite BPO Services, they debugged the company website and built supervised models including sentiment analysis.

What ties it together is a habit of connecting models to outcomes. Faiz studied computer science at the University of Mumbai and backed it with certifications in Python, SQL, AI, machine learning, and data science. They are at home in SQL across MySQL, Microsoft SQL Server, Oracle SQL, and PostgreSQL, and they visualize findings in Matplotlib, Seaborn, and Tableau. They are early in their career but already used to owning a problem from raw data through to a working tool.