Launched a mechanic data mining application with machine learning. Utilized TensorFlow for image classification and object detection, developed test samples, and trained models, establishing the company's first automated silo weight recording application.

Designed and implemented an internal company website to display key data for all raw material silos. Utilized Bootstrap framework for the front end and used Flask for the web framework. Provided users with accurate data, stable performance, and mobile compatibility.

Developed a marketing intelligence collection application leveraging big data analysis from social media. Implemented NLP for sentiment and collective analysis to evaluate network marketing prospects, extracting intelligence keywords to generate network links. For specific products and locations, derived insights and policy suggestions that increased sales force effectiveness by 20%.

Developed a scalable web application to post specialized product supply chain data for relevant users using React and Node.js, improving user engagement by 30%.

Implemented monitoring and automated alert systems, reducing web server downtime by 40% through proactive maintenance and swift issue resolution.

Led a Flour Depletion Comparison Project, designing, implementing, and managing ETL processes using Apache Spark and Apache Airflow. Integrated data from multiple sources into a centralized data warehouse on Amazon Redshift, reducing raw material inventory discrepancies by 70% monthly and improving data accessibility and analytical capabilities for stakeholders.

Optimized data workflows and ensured data quality by collaborating with cross-functional teams, conducted and engaged in tons of interviews with R&D and production leaders, and effectively communication to identify automation needs from previously overlooked data. Pioneered the use of Tableau and PowerBI for data visualization, facilitating a 50% improvement in decision-making accuracy for stakeholders.

Designed and deployed a specialized marketing database after thoroughly researching case studies and engaging with marketing staff to deeply understand campaign details. This strategic approach led to identifying key factors that made marketing campaign planning speed increased by 30%.

Developed a program to extract targeted data from JSON files into CSV using the company’s API, actively engaged with experienced colleagues to deepen understanding of the app's API, after self-teaching JSON and Python's gspread. Completed the project two days ahead of schedule.

Contributed to a research project aimed at developing assistive walking devices for the elderly, optimizing marker placement on a Vexus Vicon system over a continuous 48-hour period to enhance human posture motion data collection. Self-taught Matlab to train regression models, improving effective data capture from 30% to 80%, which resulted in a 50% reduction in the expected machine learning model training cycle due to the high-quality data.