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• Lead instructor for undergraduate and graduate courses in Data Analytics, Business Intelligence, and SQL, with a focus on Power BI, Python, and machine learning applications in real-world business contexts.
• Design and deliver curriculum that bridges theoretical knowledge with hands-on industry applications, enabling students to develop end-to-end data solutions—from data extraction and modeling to visualization and storytelling.
• Mentor students in capstone projects and research initiatives, often collaborating with industry partners to solve practical challenges in marketing, finance, and customer analytics.
• Recognized for fostering an engaging and inclusive learning environment, consistently receiving high student satisfaction ratings for clarity, relevance, and applied teaching methods.
• Continuously update course content to reflect the latest tools and trends in data analytics, including SQL databases, cloud platforms (AWS/Azure), and AI-driven business intelligence.
• Certified in Microsoft Power BI Data Analyst Associate and AWS Machine Learning, integrating industry-recognized credentials and best practices into the academic experience.

AI-Powered Document Processing Pipeline
• Architected and deployed an end-to-end OCR pipeline leveraging n8n workflow automation, PyTorch for deep learning, and GPT-4 for intelligent data extraction.
• Achieved 45% reduction in manual data entry workload and recovered 20+ hours weekly for the operations team.
• Implemented error handling, data validation, and automated quality checks, ensuring 94% accuracy in document processing.
• Technologies: n8n, PyTorch, GPT-4, Python, Docker, REST APIs

Pharma Supply Chain Optimization
• Designed and built a full-stack supply chain optimization solution combining cloud data warehousing with an interactive web application.
• Improved forecast accuracy by 15% using SARIMA time-series models, enabling proactive inventory risk identification.
• Reduced stockout incidents by 12% through predictive analytics and a real-time alerting system.
• Technologies: Python, SQL, Tableau, AWS (S3, RDS), Snowflake, predictive modeling

MLOps & Deployment
• Containerized ML models using Docker and established CI/CD pipelines for automated model testing, validation, and deployment.
• Implemented model monitoring and drift detection, reducing model deployment time from 5 days to 6 hours.
• Technologies: Docker, Kubernetes, Git, CI/CD, MLflow, model versioning

• This program uniquely bridged the gap between AI technology and business strategy, equipping me with the skills to design and deploy AI applications with a focus on responsible data governance and transparent practices. I gained a practical, action-oriented understanding of both the technical fundamentals and the human/business impacts of AI.

• This program provided me with a comprehensive skillset in emerging technologies, including: developing and deploying Internet of Things (IoT) solutions, understanding North American business practices with a focus on Montreal's tech ecosystem, and designing and implementing advanced recommender systems. Through hands-on projects and theoretical study, I gained expertise in data analysis, hardware/software integration, and collaborative filtering techniques.

• This intensive program immersed me in key data science and analytics disciplines, including data analysis, machine learning (supervised and unsupervised), and text mining. I developed proficiency in essential tools and technologies like Python, R, Tableau, and database management, applying these skills through real-world industry case studies.

• This specialized program offered in-depth training in key areas of Operations and Human Resources. I developed proficiency in Supply Chain Management, Operations Research, Service Operations Management, and Quality Management, alongside expertise in HR Analytics, Strategic Human Resource Management, and Human Resources Management. I also gained valuable knowledge in Strategic Management and Project Management.

• This four-year program equipped me with a deep understanding of mechanical engineering principles, covering a wide range of subjects including heat and mass transfer, kinematics, and automobile engineering. I developed proficiency in both theoretical concepts and practical applications, preparing me for roles in design, simulation, and control across various industries.

• Proficient in designing, implementing, and deploying machine learning solutions on AWS.
• Expertise in SageMaker, feature engineering, and model optimization.
• Skilled in ML pipeline orchestration and automated model training workflows.

• Validated expertise in AWS cloud architecture and foundational services.
• Demonstrated knowledge of AWS pricing models and cost optimization strategies.
• Proficient in deploying scalable and secure cloud infrastructure on AWS.

• Mastered building autonomous AI agents using Databricks platform.
• Implemented LLM-based agents for complex task automation and reasoning.
• Expertise in prompt engineering and agentic workflow orchestration.

• Proficient in designing and managing cloud-based data warehouses using Snowflake.
• Expertise in data modeling, query optimization, and Snowflake governance.
• Skilled in data sharing and Snowflake collaboration features.

• Expert in building generative AI applications using AWS services.
• Proficient with Amazon Bedrock, SageMaker JumpStart, and generative AI tools.
• Skilled in prompt engineering and responsible AI practices.

• Proficient in end-to-end machine learning projects using Dataiku platform.
• Expertise in visual machine learning workflows and automated model selection.
• Skilled in model deployment and monitoring within Dataiku ecosystem.

• Expert in developing custom plugins and extensions for Dataiku platform.
• Skilled in Python development within Dataiku recipe and custom component frameworks.
• Proficient in integrating external APIs and data sources with Dataiku.

• Expert in agile project management using Jira and Confluence platforms.
• Proficient in sprint planning, backlog management, and team collaboration workflows.
• Skilled in implementing agile methodologies and scaling agile practices across teams.

• Certified in designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities in Power BI.
• Proficient in DAX, Power Query, and publishing reports and dashboards for business decision-making.
• Applied directly in academic and professional contexts, including teaching BI at SKEMA Business School.

• Certified in designing and deploying production-grade agentic AI systems using LLMs and tool-calling frameworks.
• Proficient in multi-agent orchestration, memory management, and RAG pipeline architectures.
• Skilled in building reliable, evaluable AI agents for enterprise environments.

• Certified in the fundamentals of large language models, transformer architectures, and generative AI techniques.
• Proficient in fine-tuning, prompt engineering, and deploying LLM-based solutions.
• Skilled in applying generative AI to real-world NLP and multimodal use cases.

• Proficient in building and evaluating AI agents using the Databricks platform and Unity Catalog.
• Skilled in integrating LLMs with tool use, retrieval augmentation, and structured outputs.
• Experienced in deploying agent workflows for enterprise-scale data and AI pipelines.