Anzah Mehmood is a Data Scientist II at Seeloz with a background in software engineering, business intelligence, and campaign design.
Company
Anzah Mehmood currently works at Seeloz as a Data Scientist II. The company focuses on leveraging artificial intelligence and machine learning to optimize supply chain decisions. Anzah’s role at Seeloz involves developing deep learning models to enhance manufacturing and distribution processes.
Title
Anzah Mehmood holds the title of Data Scientist II at Seeloz. In this capacity, Anzah focuses on improving supply chain decisions through sophisticated machine learning models and data-driven strategies.
Education and Expertise
Anzah Mehmood earned a Bachelor of Engineering (BE) in Computer Engineering from the National University of Sciences and Technology (NUST) between 2015 and 2019. Prior to this, Anzah completed GCSE A levels at Roots IVY, studying subjects including Physics, Chemistry, Math, Economics, Sociology, and English Language. Anzah's early education concluded with GCSE O levels from Divisional Model College, where the subjects included Physics, Chemistry, Math, Biology, Economics, and Business Studies.
Professional Background
Before joining Seeloz, Anzah Mehmood accumulated diverse experience across multiple roles and companies. From 2021 to 2022, Anzah worked at Afiniti in Islamabad as a Software Engineer - AI & DA. Prior to Afiniti, Anzah held the title of Senior Officer - BI & CVM at Zong CMPak Ltd from 2019 to 2021. Additionally, Anzah co-founded The Digital Mantra and worked as a Campaign Designer from 2018 to 2019. During brief stints in 2018, Anzah also interned at Ufone in both the Human Resources and Technology departments.
Research and Development in Supply Chain Optimization
Anzah Mehmood is actively involved in researching and developing reinforcement learning environments that are tailored for supply chain modeling. This work includes creating data modeling and integration rules for new clients and devising production strategies that facilitate autonomous decision-making in supply chains. Anzah also focuses on modeling traditional supply chain scenarios to streamline operations and benchmark the effectiveness of machine learning applications.