I am a Data Science specialist with a strong engineering foundation and over a decade of experience spanning industrial automation, control systems, and modern AI-driven data science. I bring together hands-on software development, cloud-based machine learning, and business-focused analytics to deliver practical, measurable outcomes. I hold multiple industry-recognized certifications (Google, Databricks, Microsoft Azure) and combine them with formal education in Mechatronics Engineering, Instrumentation, Software Development, and Information Technology. This background allows me to bridge the gap between complex data, real-world systems, and decision-makers. As a Specialist Data Scientist, I have: Analyzed large, multi-source datasets to generate actionable insights for operational and business decisions Designed and deployed machine learning pipelines using Python, Databricks, PySpark, Azure ML Built and integrated LLM-based solutions, including custom chatbots embedded in user interfaces Delivered predictive modeling, data analysis, and visualization using PowerBI, Databricks Dashboards, and Grafana Collaborated with cross-functional teams to define data requirements, validate results, and integrate systems End-to-end ETL/ELT pipelines from logs, APIs, and databases into cloud data platforms Experience with Azure Data Explorer, Databricks, MLflow, Airflow, and cloud-native analytics Strong understanding of production ML, including experiment tracking and model lifecycle management Before fully transitioning into data science, I spent years as a Control System Engineer and Software Manager, where I: Designed and optimized industrial control systems, PLC logic, and HMI interfaces Worked directly with real-time systems, sensors, industrial communication buses, and hardware Led control software development teams in production environments This experience enables me to approach data science problems with a systems-thinking mindset, focusing on reliability, scalability, and real-world constraints—not just models.…I am a Data Science specialist with a strong engineering foundation and over a decade of experience spanning industrial automation, control systems, and modern AI-driven data science. I bring together hands-on software development, cloud-based machine learning, and business-focused analytics to deliver practical, measurable outcomes. I hold multiple industry-recognized certifications (Google, Databricks, Microsoft Azure) and combine them with formal education in Mechatronics Engineering, Instrumentation, Software Development, and Information Technology. This background allows me to bridge the gap between complex data, real-world systems, and decision-makers. As a Specialist Data Scientist, I have: Analyzed large, multi-source datasets to generate actionable insights for operational and business decisions Designed and deployed machine learning pipelines using Python, Databricks, PySpark, Azure ML Built and integrated LLM-based solutions, including custom chatbots embedded in user interfaces Delivered predictive modeling, data analysis, and visualization using PowerBI, Databricks Dashboards, and Grafana Collaborated with cross-functional teams to define data requirements, validate results, and integrate systems End-to-end ETL/ELT pipelines from logs, APIs, and databases into cloud data platforms Experience with Azure Data Explorer, Databricks, MLflow, Airflow, and cloud-native analytics Strong understanding of production ML, including experiment tracking and model lifecycle management Before fully transitioning into data science, I spent years as a Control System Engineer and Software Manager, where I: Designed and optimized industrial control systems, PLC logic, and HMI interfaces Worked directly with real-time systems, sensors, industrial communication buses, and hardware Led control software development teams in production environments This experience enables me to approach data science problems with a systems-thinking mindset, focusing on reliability, scalability, and real-world constraints—not just models.WWWW…