I am an applied data scientist and machine learning engineer with a strong foundation in analytics, AI, and operational problem-solving. I have hands-on experience working with Python, SQL, Power BI, Tableau, and machine learning tools to turn complex business and workflow challenges into practical solutions.
I currently work in IT support and operations, where I troubleshoot production systems, diagnose workflow issues, and monitor analytics to identify performance patterns. This experience has strengthened my ability to work across teams, communicate clearly, and focus on outcomes that improve day-to-day operations.
My background also includes data science and AI engineering roles where I built data pipelines, improved model performance, tested prompt variations, and supported end-to-end experimentation. I enjoy working on projects that combine technical depth with real-world impact, especially when the goal is to make systems more reliable and useful.
In addition to industry work, I have taught Python, Power BI, and SQL to university students and led project-based learning in robotics and Arduino. Teaching has helped me develop a structured, adaptable approach to explaining technical concepts and supporting learners at different levels.
I have also completed analytics and data science training through recognized programs and certifications, which has helped me build a broad toolkit across data analysis, machine learning, and visualization. I am comfortable working with both structured business data and experimental AI workflows.
I am looking for opportunities where I can contribute as a data scientist or machine learning engineer, especially in environments that value applied analytics, collaboration, and continuous improvement. I am open to roles that let me combine technical execution with business understanding and measurable impact.
Serve as the primary IT contact for Micro Fulfillment production, packing, and shipping systems. Troubleshoot issues affecting daily operations, diagnose picking errors and packing bottlenecks, monitor NEXIA Analytics, and partner with cross-functional teams on reporting and automation opportunities.
Supported pharmacy and fulfillment workflows in a Micro Fulfillment environment with strong attention to production cadence, compliance, and accuracy. Built practical knowledge of how upstream pharmacy processes affect downstream packing and shipping performance.
Improved AI model performance by revising training pipelines and evaluation methods. Tested prompt variations to improve output consistency and built data pipelines for ingestion, preprocessing, and evaluation.
Taught Python, Power BI, and SQL in a data analysis track for university students. Built and tested AI programs end to end, tuned algorithms, and guided hands-on projects from data cleaning through model evaluation.
Selected from the top 5% of applicants for a 14-week data science fellowship focused on real-world business cases. Applied Excel, SQL, Python, Tableau, and Looker Studio across analytics projects and contributed to a top-ranked capstone dashboard.
Founded a hands-on robotics and Arduino education organization to address a practical training gap for university students. Lead project-based workshops in Arduino and robotics with an emphasis on building working systems.
Supported retail merchandising activities and store execution tasks.
Handled front desk administration and customer-facing support tasks in a clinic environment.
Supported data science tasks and contributed to applied analytics work during internship.
Assisted with AI and machine learning projects, experiments, and technical development tasks.
Coached robotics on a part-time basis and supported learners in hands-on technical activities.
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