Varray Thrinath

• Developed custom machine learning models to predict business trends, aiding in strategic planning efforts.
• Assisted with the development and implementation of machine learning models designed to detect potential fraudulent activity more quickly and accurately than manual methods alone.
• Assisted in the development of machine learning models for predictive analytics, enhancing the accuracy of business forecasts.
• Leveraged cutting-edge technologies such as machine learning algorithms to enhance business intelligence capabilities in existing systems.
• Implemented advanced machine learning techniques for better understanding of complex language patterns, leading to more accurate predictions.

Completed a comprehensive 9-course program covering the fundamentals of data science, including Python programming, data analysis, data visualization, SQL, machine learning, and working with real-world data sets. Gained hands-on experience using tools like Jupyter Notebooks, Pandas, Matplotlib, and IBM Watson Studio.

• Mentored junior engineers, fostering professional growth and development within the team.
• Coordinated with suppliers and vendors, ensuring timely delivery of materials necessary for project completion.
• Demonstrated strong problem-solving skills by quickly identifying issues and implementing effective resolutions in high-pressure situations.
• Conducted thorough research to identify new opportunities for process improvements and cost reduction strategies.
• Developed innovative solutions for complex engineering challenges, enhancing project outcomes.

This workshop provided hands-on exposure to popular AI tools used in machine learning and data science. Participants explored platforms like TensorFlow, Scikit-learn, IBM Watson, and Google Colab, learning how to build, train, and evaluate basic AI models. The session emphasized practical skills in data preprocessing, model deployment, and visualization using real-world datasets.

This workshop focused on the fundamentals of Power BI, a powerful data visualization and business intelligence tool. Participants learned how to connect data sources, create interactive dashboards, build visual reports, and derive insights through data modeling and DAX functions. The session emphasized hands-on learning using real-world datasets.

• Gained foundational knowledge in Artificial Intelligence, including key concepts in machine learning, neural networks, and natural language processing.
• Participated in hands-on projects involving AI tools and frameworks to understand real-world applications.
• Collaborated with peers and mentors to solve basic AI problems and complete guided mini-projects.
• Acquired practical experience in Python programming and using AI libraries such as TensorFlow or Scikit-learn.

• Supported staff members in their daily tasks, reducing workload burden and allowing for increased focus on higher-priority assignments.
• Gained valuable experience working within a specific industry, applying learned concepts directly into relevant work situations.
• Analyzed problems and worked with teams to develop solutions.
• Contributed to a positive team environment by collaborating with fellow interns on group projects and presentations.