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I'm an AI/ML lead with years of applied development experience across modeling, large-scale data pipelines, and MLOps, paired with deep expertise in risk management for AI solutions. I'm driven by solving real-world challenges, and I apply rigorous data processing, benchmarking, testing, and documentation practices to ensure models are performant and reliable, enabling confident business decisions and strong governance outcomes. I partner closely with product, engineering, and risk/compliance stakeholders to align roadmaps, define acceptance criteria, and deliver production-ready, audit-ready solutions, while incorporating best practices that improve delivery speed and measurable outcomes on large-scale data.…I'm an AI/ML lead with years of applied development experience across modeling, large-scale data pipelines, and MLOps, paired with deep expertise in risk management for AI solutions. I'm driven by solving real-world challenges, and I apply rigorous data processing, benchmarking, testing, and documentation practices to ensure models are performant and reliable, enabling confident business decisions and strong governance outcomes. I partner closely with product, engineering, and risk/compliance stakeholders to align roadmaps, define acceptance criteria, and deliver production-ready, audit-ready solutions, while incorporating best practices that improve delivery speed and measurable outcomes on large-scale data.

Parsa Farshadfar

Data Scientist, AI Engineer, Full Stack Developer, +5

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I'm an AI/ML lead with years of applied development experience across modeling, large-scale data pipelines, and MLOps, paired with deep expertise in risk management for AI solutions. I'm driven by solving real-world challenges, and I apply rigorous data processing, benchmarking, testing, and documentation practices to ensure models are performant and reliable, enabling confident business decisions and strong governance outcomes. I partner closely with product, engineering, and risk/compliance stakeholders to align roadmaps, define acceptance criteria, and deliver production-ready, audit-ready solutions, while incorporating best practices that improve delivery speed and measurable outcomes on large-scale data.…I'm an AI/ML lead with years of applied development experience across modeling, large-scale data pipelines, and MLOps, paired with deep expertise in risk management for AI solutions. I'm driven by solving real-world challenges, and I apply rigorous data processing, benchmarking, testing, and documentation practices to ensure models are performant and reliable, enabling confident business decisions and strong governance outcomes. I partner closely with product, engineering, and risk/compliance stakeholders to align roadmaps, define acceptance criteria, and deliver production-ready, audit-ready solutions, while incorporating best practices that improve delivery speed and measurable outcomes on large-scale data.

Available to hire

I’m an AI/ML lead with years of applied development experience across modeling, large-scale data pipelines, and MLOps, paired with deep expertise in risk management for AI solutions.

I’m driven by solving real-world challenges, and I apply rigorous data processing, benchmarking, testing, and documentation practices to ensure models are performant and reliable, enabling confident business decisions and strong governance outcomes. I partner closely with product, engineering, and risk/compliance stakeholders to align roadmaps, define acceptance criteria, and deliver production-ready, audit-ready solutions, while incorporating best practices that improve delivery speed and measurable outcomes on large-scale data.

Skills

Experience Level

Expert

Expert

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Expert

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Expert

Language

English

Fluent

Work Experience

Academic Tutor at York University

June 1, 2024 - December 1, 2025

Led weekly tutorials for the Design and Analysis of Algorithms course, breaking down complex concepts into practical problem-solving strategies to boost student comprehension. Orchestrated exam review sessions, guiding peer-to-peer technical discussions and fostering a collaborative problem-solving environment.

Senior Machine Learning Scientist at TD Bank

May 1, 2024 - Present

Led end-to-end delivery of production ML models, defining technical direction from problem framing and requirements through deployment, monitoring, and iteration. Owned the model development lifecycle operating model, establishing clear stage gates, artifacts, and handoffs to accelerate delivery while improving consistency. Partnered with Risk, Compliance, and Technology stakeholders to ensure audit-ready solutions by design, aligning documentation, testing evidence, and approvals with governance expectations. Set roadmap and priorities for a portfolio of ML deliverables, balancing business impact, engineering effort, and operational risk. Standardized reusable components to reduce rework and increase adoption. Drove quality and reliability practices across ML development including data profiling, data drift, performance monitoring, explainability, bias/fairness, reproducibility, versioning, and production monitoring. Provided technical leadership and mentorship to scientists and engin

Data Scientist II at TD Bank

February 1, 2022 - May 1, 2024

Built repeatable data pipelines and feature datasets, applying data quality checks and documentation to improve reliability and reuse. Built and maintained AI/ML models (PyTorch, TensorFlow, XGBoost, LLMs, Scikit-learn) in clean modular code with efficient version control. Monitored post-release performance using defined KPIs and feedback loops, triaging issues and recommending retraining or corrective actions based on pre-approved action plans. Produced clear report artifacts to support governance reviews and future maintenance. Improved team efficiency by contributing reusable code, templates, and internal knowledge transfer meetings (how-tos, runbooks, and workshops).

Machine Learning Researcher at York University

September 1, 2019 - November 1, 2021

Developed the Spiking Convolutional Neural Network (SCNN), an energy-efficient deep learning method for automated seizure detection, leveraging spatio-temporal features from multichannel EEG time-series data to achieve state-of-the-art precision and recall. Reduced computational costs by 40%, making the AI process viable for low-power portable medical devices.

Data Scientist at Divar

April 1, 2017 - January 31, 2018

Leveraged deep learning and machine learning techniques to enhance user experience and efficiency, analyzing datasets exceeding 10 TB. Boosted click-through rates (CTR) by 4% and improved Return on Ad Spend (ROAS) by 3% through data-driven strategies and precision-targeted advertising initiatives. Transformed over 50 large-scale SQL datasets for analysis using ETL, and created over 7 interactive dashboards and visualizations to facilitate decision-making.