Student Perspectives: Adapting to a Dynamic Industry

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MS Statistics ‘24 student, Wenxin Zhan, shared with the GCMC how a remote internship helped to expand skills, knowledge, and network in the tech industry.

1. One of the most important things I’ve learned at my internship:

The most critical lesson from my internship in a rapidly evolving technology industry is the significance of continuous growth and learning. Technology is dynamic, with constant advancements and shifts. Staying updated with the latest technologies, methodologies, and industry trends is essential. This not only involves enhancing technical skills but also adapting to new ways of problem-solving and innovating. Embracing this ever-evolving learning curve is vital for personal and professional development in the technology sector.

2. Networking Strategy in a Remote Internship:

Networking in a remote internship requires innovative approaches, especially in a small company where everyone works remotely. My strategy involves active participation on Slack, contributing to tasks, and engaging in meaningful conversations with colleagues. As an example, I arranged private meetings with colleagues following our manager’s meetings. These sessions were dedicated to discussing action plans and task allocation, fostering a collaborative work environment despite the physical distance.

3. My Biggest Contribution:

My key contribution to the team has been enhancing the accuracy and depth of our data analyses. I focused on ensuring data accuracy and integrity and exploring various facets of the data, leading to more comprehensive and reliable insights. This involved awareness of data privacy issues, meticulous examination on implementation and verification on data output, critical questioning, and fostering a collaborative environment for innovative ideas. These efforts have significantly improved the quality and effectiveness of our analyses, making them more robust, accountable and insightful.

4. Future Learning Aspirations:

Post-internship, I am eager to delve deeper into Large Language Models (LLM) and expand my expertise in model building. My interest lies in exploring tools like TensorFlow, PyCarret, PyTorch, Statsmodel, and XGBoost. These advanced tools offer powerful capabilities in machine learning and data analysis, and mastering them will significantly enhance my skills as a data scientist.

5. Advice for Students Struggling to Find Internships:

For students facing difficulties in securing internships, my advice is to enhance skills and knowledge relevant to their desired industry continuously. In the tech sector, for instance, expertise in Natural Language Processing (NLP), Large Language Models (LLM), Machine Learning (ML), and cloud computing is highly sought after. Being proficient in these areas can significantly boost a candidate's appeal.

It's also crucial to analyze job descriptions in the target field, identifying the skills and qualifications most in demand. This information should guide your learning path, ensuring that you're developing competencies that align with market needs. Beyond technical skills, soft skills like effective communication and problem-solving are also important.

Networking is another key strategy. Building connections on platforms like LinkedIn or through industry events can open doors to opportunities. It's more than seeking job openings; it's about learning from others, gaining industry insights, and building supportive relationships.

Lastly, improving oral communication and thoroughly understanding your projects enhance your performance in interviews and the workplace. Being able to clearly and effectively communicate your work and results to those who may not have a professional background in your field is vital.

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