Faisal Mohammed
Dallas,TX
Summary
- Experienced Data Scientist with a Master’s in Artificial Intelligence from the University of North Texas, currently based in the U.S. and holding Indian citizenship. I bring deep expertise in machine learning, MLOps, and Generative AI (LLMs, RAG, GANs), with hands-on experience building scalable solutions for dynamic pricing, computer vision, and intelligent automation.
- Fluent in Python, AWS, TensorFlow, and modern NLP frameworks like LangChain and GPT, I’ve led end-to-end AI initiatives—from designing ML pipelines to deploying production-ready chatbots that streamline user engagement and decision-making. My approach balances technical innovation with real business impact.
- Conversant in Arabic and fully open to relocating, I’m strongly motivated to contribute to Saudi Arabia’s evolving AI ecosystem. I’m excited to support Vision 2030 by bringing data-driven solutions that empower industries and transform operations.
Overview
4
4
years of professional experience
1
1
Certification
Work History
Data Analyst
Navon Tech
Dallas, TX
07.2024 - Current
- Developed in-house applications to maintain profit and loss data for real estate properties, leveraging SharePoint for data management and Power BI/Tableau dashboards for real-time visualization.
- Contributed under multiple roles in a startup real estate company, creating strategic solutions that improved data accuracy and operational efficiency.
- Created and refined organization strategies and documentation in compliance with government standards, partnering closely with leadership for reviews and approvals.
- Implemented AI/ML models (including EDA and Data Science workflows) to analyze public feedback data, identifying optimal areas for real estate investments.
- Conducted regular data quality assessments, maintained issue resolution logs, and worked cross-functionally with leadership to prioritize key resolutions.
- Built an innovative chatbot powered by advanced ML algorithms, enhancing user experience and stakeholder engagement.
Faculty – TA under Professor Ravi Vadapalli
University of North Texas
08.2023 - 05.2024
- Collaborated with a professor to design an engaging learning environment that leveraged data-driven insights to enhance student outcomes.
- Developed and maintained SQL databases for efficient data storage, retrieval, and big data processing.
- Performed exploratory data analysis (EDA) using Python libraries (e.g., Pandas, NumPy) to derive actionable insights.
- Created data visualizations with Matplotlib and Seaborn, effectively communicating analysis results to diverse audiences.
- Applied data science methodologies to manage and analyze large datasets, driving data-informed decision-making and continuous improvement.
Faculty – GRA along with Dr. Aleshia Hayes
University of North Texas
02.2023 - 07.2023
- Served as a Graduate Research Assistant under Dr. Aleshia Hayes, conducting data analysis and NLP-based sentiment analysis on YouTube 360 videos and Reddit comments.
- Built predictive models using Python (Pandas, scikit-learn, NLTK) and machine learning techniques to derive actionable insights from user-generated content.
- Leveraged big data technologies like Hadoop and Spark for efficient processing of large-scale datasets, optimizing data pipelines and workflows.
- Contributed to automated reporting systems using Python and SQL, integrating data extraction, transformation, and visualization for enhanced decision-making.
Cognitive Data Scientist
IBM
Bengaluru, Karnataka
10.2021 - 12.2022
- Led research on Generative Adversarial Networks (GANs), developing novel architectures that reduced data augmentation costs by 60%, all within an Agile framework.
- Collaborated with cross-functional teams to architect and deploy scalable ML systems, including custom transformer models and advanced neural network architectures.
- Pioneered the integration of Retrieval Augmented Generation (RAG) systems with enterprise knowledge bases, boosting response accuracy by 40% while maintaining strict data privacy.
- Built and optimized production-grade deep learning models using PyTorch and TensorFlow, focusing on computer vision and NLP tasks.
- Developed automated MLOps pipelines for model training, validation, and deployment using Kubeflow and MLflow, cutting deployment time by 70%.
- Leveraged AWS cloud technologies and ML tools to ensure efficient data scaling, cost optimization, and robust performance in live production environments.
Education
Master of Science - Artificial Intelligence
University of North Texas
Dallas,TX07.2024
Bachelor of Technology - Computer Science And Engineering
NIIT University
Neemrana, Rajasthan05-2022
Skills
- Python
- HTML5, CSS, Django, Flask
- SQL
- Data analysis, Natural language processing, Data visualization
- Machine learning, Chatbot
- TensorFlow, Keras, Pytorch
- Tableau, Power BI
- Docker, Kubernetes
- Azure, AWS
- NumPy, Pandas, Scikit-learn, Matplotlib
- MLOps
- Generative AI, LLM, RAG
- Time Series Analysis
- Problem solving
- Team player
- Clear communicator
- Leadership skills
- Analytical skills
Projects
- Advanced Stock Market Prediction using Multi-Modal AI: Developed a sophisticated stock prediction model integrating technical analysis, sentiment analysis, and macroeconomic indicators. Leveraged LSTM networks for time series forecasting of stock prices, achieving a 20% improvement in prediction accuracy compared to traditional models. Utilized feature engineering to incorporate macroeconomic data, enhancing the model's ability to capture market trends. Authored a comprehensive research paper detailing the methodology and findings, currently under review for publication.
- Dynamic Pricing for Restaurants using Artificial Intelligence and Deep Learning: Architected a hybrid system combining GANs and RAG to revolutionize restaurant pricing and menu optimization, leveraging historical data and real-time market conditions. Developed a custom GAN architecture that generates synthetic customer behavior patterns, enabling robust price testing without real-world experimentation. Implemented a RAG system that retrieves and analyzes contextual data from multiple sources (competitor pricing, local events, weather patterns, social media sentiment) to inform the generative model, resulting in a 35% improvement in price optimization accuracy. The combined GAN-RAG system demonstrated remarkable results: 28% increase in profit margins, 15% reduction in food waste through better demand prediction, and 40% improvement in customer satisfaction scores through more balanced pricing.
- Generating Authentic Reviews using Artificial Intelligence (SumRiseAI): Developed an automated review analysis platform using Python, TensorFlow, and advanced NLP techniques to parse thousands of online reviews within seconds. Integrated Generative Adversarial Networks (GANs) and Retrieval Augmented Generation (RAG) to provide human-like understanding of review sentiment, detect fake feedback, and identify genuine patterns. Streamlined data processing, reducing hours of manual review to a concise 30-second scan, enabling clients to capture critical customer insights without data overload. Incorporated external market context to deliver a complete, unbiased overview of product or service perception, boosting data-driven decision-making for stakeholders.
- Designed and deployed a bilingual (Arabic-English) chatbot to automate customer support and user onboarding for a Saudi AI-focused FinTech company. Built custom NLU models with Rasa and fine-tuned Arabic language transformers for accurate intent recognition and entity extraction. Integrated with CRM systems via REST APIs and deployed on AWS Lambda using FastAPI for scalable performance. Implemented real-time analytics and feedback loop for model retraining using MongoDB. Achieved 89%+ accuracy on Arabic queries, reduced support load by 52%, and improved onboarding completion rate by 41%.
Certification
- Career Essentials in Data Analysis, Microsoft LinkedIn Learning – Jan 2025
Gained practical skills in data analytics, visualization techniques, and interpreting data to support decision-making. Covered tools and concepts commonly used in business analytics roles. - Power BI: Dashboards for Beginners LinkedIn Learning – Jan 2025
Completed practical training on building interactive dashboards using Microsoft Power BI. Learned essential dashboard design techniques and data storytelling for business users.
Languages
English
Full Professional
Arabic
Full Professional
Urdu
Native/ Bilingual
Telugu
Limited
Timeline
Data Analyst
Navon Tech
07.2024 - Current
Faculty – TA under Professor Ravi Vadapalli
University of North Texas
08.2023 - 05.2024
Faculty – GRA along with Dr. Aleshia Hayes
University of North Texas
02.2023 - 07.2023
Cognitive Data Scientist
IBM
10.2021 - 12.2022
Master of Science - Artificial Intelligence
University of North Texas
Bachelor of Technology - Computer Science And Engineering
NIIT University