Data Scientist & AI / ML Engineer with 5+ years of experience in medical computer vision & AI, demand forecasting and consulting.

* SOTA CV: large vision and multimodal models, language guided segmentation & detection * Frontier research in AI: world models, reasoning in representation space

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Anton Gribanov is a versatile professional with experience as a Financial Advisor and Sales Manager. Based in North York, Ontario, he is currently self-employed and open to new opportunities in full-time and contract work. With 7 years of professional experience, Anton has worked in financial services and real estate, demonstrating a diverse skill set. He holds educational background from SPbSUSE and has studied International Business in BUU, with additional courses from MITx. Anton's professional interests include machine learning in finance, market analysis, and customer relations. He maintains a GitHub repository focused on Machine-Learning-in-Finance, showcasing his technical skills and commitment to integrating financial expertise with data-driven solutions.

Machine learning in finance, financial modeling, data analysis, international business, real estate, sales management, customer relations, market analysis.

Actively seeking full-time and contract opportunities in data science and financial technology. Developing technical skills in data analysis, financial modeling, and applying machine learning techniques to financial datasets.

Razy Shafiee is an innovative AI and Machine Learning Engineer based in Toronto, Canada, with over five years of experience building scalable ML-driven systems. She holds a Master’s degree in Mathematics and Statistics from Dalhousie University and a Master’s degree in Computer Science from Sharif University of Technology. Razy has led cutting-edge AI projects across wealth management, stock prediction, and semantic search, specializing in deep learning, graph algorithms, and Agentic AI. Passionate about real-world impact, he combines strong technical expertise with strategic thinking to deliver high-performance AI solutions.

I am passionate about scalable AI systems, real-time LLM pipelines, and graph-based machine learning, especially for financial and multi-agent applications. I am eager to connect with collaborators building innovative solutions in wealth management, RAG, and Agentic AI.

I am currently leading the design of scalable AI models for wealth management at Prospera AI, focusing on integrating Agentic AI frameworks like A2A and MCP. In parallel, I'm refining a hybrid stock prediction system built with Galformer and MemGPT, optimizing real-time LLM pipelines and retrieval augmented generation (RAG) strategies. I am also researching advanced Graph RAG methods to enhance semantic search and content retrieval architectures.