I am currently pursuing my Masters in Computer Science with a specialization in Data Science at Seattle University.

As a Graduate Research Assistant at the University, I am involved in developing personalized health risk prediction through transfer learning techniques. I am working on a framework that provides a systematic and detailed approach, integrating transfer learning techniques and neural network models for personalized health assessments. In an effort to boost the predictive accuracy of the model, I used feature engineering within the neural network architecture. Leveraging base classification models, these engineered features were used as input, resulting in a remarkable 10% improvement in overall accuracy.

In my part-time role as a Data Analyst on campus, I collaborated closely with underserved local businesses in Seattle's Central Area. Engaging with cross-functional teams, offering project management assistance, and extending technical support were integral aspects of my contributions. Notably, I excelled in collecting and analyzing client data through APIs and client files, leveraging Python and PowerBI to generate meaningful insights encapsulated in interactive dashboards.

Additionally, I bring over 4 years of professional experience. During my time at Deloitte and Infor, I played a pivotal role in configuring and integrating financials and supply chain management with CRM systems, aligning them with our clients' unique business needs. I ensured data flow integrity by extracting and transforming data from diverse sources. and excelled in data analysis, by producing insightful reports and created Supplier performance dashboards.

My passion for technology has driven me to acquire expertise in programming languages such as Java and Python, alongside proficiency in machine learning techinques and analytical tools like Power BI and Tableau. Designing Restful APIs and working with SQL and MongoDB databases are among my skill set, I effectively derive valuable insights from extensive datasets using Bigdata Technologies like Spark, kafka and AWS services.

I'm expected to graduate in March 2024, actively seeking software engineering and data centric roles where I can bring impactful contributions to your team.

Thank you for your consideration.