Personal Summary

Senior Data Scientist with strong experience in machine learning, NLP, time series analysis, and data-driven product development. Passionate about building practical intelligent systems, solving business problems with data, and contributing to innovative teams through technical depth, project execution, and applied research.

Management and Collaboration Skills

• Project management and team workspace tools: Jira, Trello
• Cross-functional collaboration
• Project planning, execution, and delivery
• Effective communication and coordination
• Outcome-oriented mindset and decision-making
• Time management and prioritization
• Collaborative problem solving in technical environments

Technical Skills

• Machine Learning Frameworks: PyTorch, TensorFlow, Scikit-Learn
• Programming Languages: Python
• Data Manipulation: Pandas, NumPy
• Deep Learning: Neural Networks, CNNs, RNNs, LSTM, GRU, Transformers
• Natural Language Processing: NLTK, SpaCy, Hazm
• Data Visualization: Matplotlib, Seaborn, Plotly, Dash, Bokeh
• Model Deployment: Docker, Kubernetes
• Big Data Tools: Spark
• Version Control: Git, GitHub
• SQL Databases: MySQL, SQLite, SQL Server
• Feature Engineering and Data Preprocessing
• Model Evaluation and Hyperparameter Tuning
• NLP, Time Series Analysis, Dynamic Pricing, Computer Vision

Senior Dynamic Pricing Data Scientist / Khanoumi, Tehran, Iran

Mar 2025 - Current

• Built and deployed a dynamic pricing system for automated daily price recommendation.
• Designed a pricing engine that learns price-demand behavior while respecting discount guardrails and cost floors.
• Integrated pricing recommendations with campaign planning workflows.
• Contributed to data-driven pricing decisions through practical machine learning solutions.

Senior Machine Learning Engineer (NLP, Time Series) / Securities and Exchange Organization of Iran

Aug 2021 - 2025

• Developed anomaly detection models on order-flow features to identify suspicious market behavior.
• Designed a Persian social media monitoring system for finance-related hashtags and market sentiment tracking.
• Built real-time monitoring pipelines and dashboards using external and internal market data feeds.
• Worked on NLP and time series solutions for market surveillance and analysis.
• Contributed to project planning and execution for monitoring and analytics products.

Founder & Full-Stack Developer with Machine Learning Expertise / Nemad Bin Bot, Sharif University of Technology, Tehran, Iran

2020 - 2023

• Designed and implemented a Persian natural language to visualization pipeline: NLP → SQL Query → Python Code → Visualization.
• Built scalable software architecture with strong system reliability considerations.
• Designed a high-performance MySQL database for intensive read-write operations.
• Developed a high-speed web crawler for efficient data extraction and storage.
• Analyzed user logs and usability patterns and contributed to attracting more than 10,000 monthly active users.
• Tools: Python, PyTorch, Telegram Bot, MySQL, NLTK, Plotly

Machine Learning Engineer / Taha Startup Studio, Sharif University of Technology, Tehran, Iran

2017 - 2021

• Developed basic NLP tools in both Persian and English.
• Led the creation of a fine-grained Persian sentiment analysis dataset with more than 43,000 sentences and five-class labels.
• Contributed to sentiment analysis model development based on the dataset.
• Developed a video game-playing agent using CNN-based image processing approaches.
• Tools: Python, PyTorch, LSTM, GRU, CNN, Image Processing

Machine Learning Research Engineer / Department of Economics and Management, Sharif University of Technology, Tehran, Iran

2019

• Created a model to predict time series data for 10 stock market shares.
• Tools: PyTorch, NumPy, RNN

Co-founder and Machine Learning Engineer / Sibe Sorkh, MCS Department, Allameh Tabataei University, Tehran, Iran

2016 - 2017

• Developed and trained a text classification model to distinguish homeowner ads from real estate agent ads.
• Built a pipeline to crawl, clean, and analyze web data with more than 10,000 rows processed daily.
• Tools: Python, Scrapy, Requests, Selenium, BeautifulSoup, UrlLib

Game Developer / Amin Intelliware, Tehran, Iran

2012 - 2015

• Video game developer.
• Augmented Reality developer.

Uber's Contribution to Faster Deep Learning, A Case Study in Distributed Model Training

Chapter published in Advances in Data Clustering: Theory and Applications, Springer.

Author: Hamid Mahmoodabadi

PSA43K: A Fine-Grained Persian Sentiment Analysis Dataset

Under ACL Rolling Review.

First Author: Hamid Mahmoodabadi

Co-author: Leila Afsar

Supervisor: Ahmed M. Abdelmoniem, Queen Mary University of London

Research contribution: creation of a Persian sentiment dataset with 43,000+ sentences and fine-grained five-class labels.

Evaluation the Effect of the Dimension Reduction on the Performance of Linear and Non-linear Classifiers

Conference paper, July 2017.

First Author: Hamid Mahmoodabadi

Supervisor: Mohammadreza A. Oskoei, University of Essex

Glossary of Data Science and Machine Learning Terms

GitHub repository, July 2023.

Author: Hamid Mahmoodabadi