Avinash Navlani
Technical Architect - Data Science @PETRONAS
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WORK HISTORY
Technical Architect - Data Science @PETRONAS
Kuala Lumpur City, MY
Designed and implemented an Integer Programming model to optimize road tanker routing and scheduling, enhancing efficiency in daily order fulfillment from depots to terminals- Developed a flexible rescheduling logic for manual adjustments, allowing business users to modify schedules in real-time to accommodate changing demands.
EDUCATION
Rajiv Gandhi Prodyogiki Vishwavidyalaya
Bachelor of Engineering - BE, Information Technology
Devi Ahilya Vishwavidyalaya
Master of Technology , Data Science and Operations Research
SKILLS
ABOUT AVINASH NAVLANI
With over 8 years of experience in Data Science, AI, and Operations Research, I have worked across the entire ML pipeline—data preprocessing, feature engineering, model development, evaluation, and deployment in cloud environments (Azure, AWS, and GCP). Currently, I’m a Senior Data Scientist, leveraging advanced analytics, optimization techniques, and big data tools to enhance products and services. My work involves building and maintaining ML models, deploying research-driven solutions for decision-making, and operationalizing AI at scale.I have led end-to-end machine learning and optimization projects, applying Operations Research techniques (Gurobi) to solve complex business problems. Additionally, I bring hands-on data engineering experience, designing and implementing scalable ETL/ELT pipelines.My expertise spans Machine Learning, NLP, Large Language Models (LLMs), Time Series Forecasting, MLOps, and Data Engineering, with proficiency in Python, PySpark, SQL, Airflow, Databricks, and cloud computing platforms. I have a solid foundation in software engineering, including object-oriented programming (OOP), API development (FastAPI, Flask), containerization (Docker, Kubernetes), and CI/CD pipelines for automating ML model deployment and monitoring.Competencies: Data Science, Machine Learning, NLP, LLM, Python, PySpark, Hive, AirFlow, MLOps, Operations Research, Gurobi, GCP, Azure, AWS, ETL Pipeline, Databricks.
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