About Me.
Data Scientist and Machine Learning Specialist with end-to-end experience across the ML lifecycle—from data extraction and transformation to model development, deployment, and monitoring. Skilled in statistical analysis, predictive modeling, NLP, and deep learning, with a strong track record applying LLMs, RAG pipelines, and scalable cloud-based solutions to drive business value. Passionate about turning data into actionable insights that enhance decision-making and user experience.
Certificates
I am passionately dedicated to expanding my knowledge in the realms of data science and machine learning, as evidenced by the array of certificates I have diligently earned. These achievements serve as a testament to my unwavering commitment to self-improvement and proficiency in these cutting-edge fields. Motivated by an intrinsic drive for learning, I have taken the initiative to acquire valuable skills and insights independently.
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AWS Machine Learning Speciality Certificate (2025)
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IBM Data Science Professional Certificate
Including courses: Data Analysis, Data Visualization, Databases
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IBM AI Engineering Professional Certificate
Including courses: Deep Learning with Keras, Neural Network with Pytorch,
Deep learning with Tensorflow, Image processing
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Machine Learning Specialization (Stanford University)
Including courses: Supervised and Unsupervised Machine Learning
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DataCamp Data Science with Python Certificate
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DataCamp Machine Learning Scientist with Python Certificate
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Including courses: Cluster Analysis, Feature Engineering, NLP, Deep Learning
Experience
Data scientist / Machine Learning Engineer
ActiveDEMAND
Apr 2024 - Present
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Design and deploy multi-layer Deep Learning Keras and PyTorch Models such as TimeLSTM, LogisticHazard and DeepHit + RNN Survival Models to predict the optimal next marketing task and timing for contact conversion using multi-input sequential data that improved contact conversion prediction accuracy by over 10% in A/B tests.
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Developed NLP-driven predictive models with XGBoost to optimize content engagement, personalization and customer interaction
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Deployed end-to-end machine learning pipelines on AWS SageMaker, integrating feature engineering, model training, batch inference, and real-time API deployment
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Data Engineered ETL workflows with AWS Glue & PySpark, transforming high-dimensional marketing data into actionable insights
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Manage AWS SageMaker MLOps for real-time and batch inference, optimizing model performance, cost efficiency, and scalability
Selected Freelance Projects
ML Engineer
Jun 2023 - Current
Developed Retrieval-Augmented Generation (RAG) pipelines using Hugging Face and custom vector stores like OpenSearch to deliver context-aware responses.
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Fine-tuned LLMs from Hugging Face models for generative AI applications in marketing automation, enhancing personalization and engagement strategies.
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Deployed and managed fine-tuned models using AWS SageMaker endpoint
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Implemented MLOps best practices with MLflow for experiment tracking, model versioning, and performance monitoring, ensuring reproducibility and continuous improvement.
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Collaborated with backend and DevOps teams to integrate ML models into production APIs, ensuring seamless deployment and scalability.
Architect / Data science researcher
Perkins and Will, Calgary, AB
Jan 2021 - Feb 2024
Led interdisciplinary research at the intersection of architecture, data science, and sustainability.
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Processed time-series data from IoT sensors, leading to the creation of an anomaly detection system that reduced equipment downtime by 15%.
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Successfully loaded, processed, and merged data from EnergyPlus models, resulting in improvement in energy efficiency for the analyzed buildings.
Education
2018-2020
University of Calgary
Master of Architecture Engineering
2013-2015
University of Tehran
2008-2013
SHarif University of Technology
Master of Architecture
Bachelor of Civil Engineering
