Summary
Najib Ishaq is an Algorithmic Data Analysis Consultant with eight years of experience blending rigorous applied mathematics and practical data science to tackle large-scale data problems. He has a research-driven background in anomaly detection, sub-linear search, and dataset compression, with work extending to 3D object recognition from point clouds and an IEEE publication since 2019. Najib moves ideas from theory to production, having served as a data scientist at Axle Informatics and conducted long-term research at the University of Rhode Island before transitioning to independent consulting. He is comfortable with both algorithmic innovation and programming implementation, enabling efficient solutions for high-volume, resource-constrained environments. Based in West Warwick, RI, he pairs academic training from Brown and URI with hands-on experience that favors signal-efficient, scalable approaches over brute-force engineering. An understated strength is his focus on sub-linear techniques that reduce computational cost while preserving analytic fidelity—valuable for clients facing ever-growing datasets.
8 years of coding experience
7 years of employment as a software developer
Applied Mathematics, Applied Mathematics at Brown University
Data Science, Data Science at University of Rhode Island