Aamir Khan

• MLOps/ML Engineer at Definity Financial with 4 years of hands-on experience
• Specialist in GenAI/LLM with expertise in implementing and deploying end-to-end pipelines.
• Worked on a diverse set of problems from underwriting, claims, and fraud analytics related to both personal and commercial insurance.
• Master's in data science graduate from the University of British Columbia (UBC).

I welcome any opportunity that allows me to dig deeper, play with data to improve decision-making, building end-to-end pipelines on various Cloud platforms.

Approximately 4 years of professional experience. His experience is centered on MLOps/ML Engineering within the financial industry.

Intermediate MLOps Engineer at Definity Financial (July 2024 – Present): Leading the design and implementation of a project to process commercial policy quotes using Google GenAI services. Implemented a machine learning pipeline for underwriting using Google's Vertex AI.

Advanced Analytics Professional at Definity Financial (June 2022 – June 2024): Involved in implementing and deploying a claims fraud flagging model. Refreshed models for online insurance tools. Worked on migration of processes to the Google Cloud Platform. Refactored a Usage-based Insurance (UBI) ML pipeline.

Data Scientist at PLC Group (Oct 2021 – May 2022): Worked as a data specialist with logs and telemetry data from communication tower devices. Involved in data cleansing, integration, feature selection, and model development, using Google Cloud Platform services.

Master of Data Science, The University of British Columbia, Canada (Sept 2020 - June 2021): A Master's degree specifically in Data Science, indicating formal training in relevant analytical techniques. The coursework included Data Wrangling, Algorithms & Data Structures, Data Visualization, Statistical Inference, Machine Learning, and Cloud Computing – all highly relevant to a data analyst position.

PhD.

Computer

Science, University of Nice Sophia Antipolis, France (Nov 2006 - Mar 2010): While older, the Ph.D. in Computer Science demonstrates a strong foundational understanding of computer science principles, algorithms, and potentially data-related topics (depending on the specifics of his research). The thesis, "Model-based Design for On-chip Systems: Using and Extending MARTE and IP-Xact," shows experience with modeling and complex systems design, which could be transferrable to data modeling.