About Me

Welcome to a deep dive into my professional journey and expertise. I am AliReza Zarreh, a Data Scientist committed to leveraging advanced analytics to drive transformation in the retail industry. With a robust academic background and extensive field experience, my mission is to harness the power of data to optimize business outcomes and catalyze growth.

• Ph.D. in Mechanical and Manufacturing Systems Engineering
  University of Texas at San Antonio, Klesse College of Engineering, 2019
  Specialized in cybersecurity in manufacturing, with a focus on advanced predictive modeling and operational efficiency.
• M.Sc. in Mechanical Engineering (Mechatronics and Control Systems focus)
  University of Tehran, Faculty of Engineering, 2008
  Gained profound technical and analytical skills, focusing on innovation and problem-solving in engineering contexts.

• Programming Languages & Development: Advanced expertise in Python, R, SQL, and Scala for data science and analytics applications. Practical knowledge in Java and C++ for comprehensive software development and algorithmic solutions.
• Machine Learning & Deep Learning: Proficient in employing deep learning frameworks like TensorFlow, Keras, and PyTorch for predictive modeling and forecasting. Skilled in machine learning algorithms via Scikit-learn, XGBoost, and Spark MLlib for scalable solutions.
• Generative AI & Large Language Models: Deep understanding of transformer-based architectures with hands-on experience in fine-tuning large language models (OpenAI, GPT variants). Expert in applying Retrieval-Augmented Generation (RAG), prompt engineering, and conversational AI to deliver innovative, scalable AI solutions.
• Big Data Technologies: Expert in using Spark, Hadoop, and Ray for data processing and distributed computing at scale, enabling efficient analysis of massive datasets and real-time processing capabilities.
• Cloud Computing & MLOps: Demonstrated expertise in cloud platforms like GCP, AWS, and Azure Databricks. Proficient in deploying scalable ML models using Vertex AI for ML pipelines and implementing robust MLOps practices with CI/CD processes.
• Data Architecture & Engineering: Competent in designing and implementing robust data architectures, ensuring data quality and accessibility. Experienced in using Dataform for data modeling and preprocessing workflows, creating reliable data pipelines for analytics.
• Optimization & Quantitative Analysis: Strong background in optimization techniques, time-series analysis, and statistical modeling. Expert in mathematical modeling and hypothesis testing to support data-driven insights, particularly in retail and e-commerce contexts.
• Leadership & Collaboration: Proven ability to lead cross-functional teams and collaborate with stakeholders to drive data-driven decision-making. Effective mentor to junior data scientists and interns, fostering a culture of learning and innovation.

My approach to data science is rooted in a deep understanding of both the technical and business aspects of the field. I believe in the transformative power of data to drive better decisions, create value, and foster innovation. As a Data Scientist, I am dedicated to bridging the gap between complex data analysis and practical business applications, ensuring that data insights lead to actionable and impactful outcomes.

As I continue to grow in my career, I aim to further enhance my impact in the retail industry, developing innovative solutions that address key challenges and drive progress. I am also passionate about sharing my knowledge and insights, mentoring emerging talents, and contributing to the broader data science community.