Hi there, I am also a Master's student in Data Science. In my spare time, I try to work on projects related to data science or data engineering. My most recent major project (still unfinished) involves creating a Dockerized container for Kafka streaming, Flink (for data transformation), and Apache Druid (for big data storage). This project constructs a data pipeline for sentiment analysis. I have also worked on other Dockerized streaming and non-streaming data pipelines for environmental and climate/weather data collection. These projects integrate JupyterLab and Apache Spark (for data processing similar to Jupyter Notebook with machine learning library integrations and tailored towards big data handling), alongside data warehousing options for structured and semi-structured data. For these projects, I have often chosen Docker for academic purposes, as it makes configuration and deployment easier to handle by being more system-agnostic. If you'd like to learn more or collaborate, just let me know; I'd be more than happy to help!
Christopher M Overton Hi, thanks for sharing your projects! They sound fascinating! My experience is more focused on later stages of data analysis, so I have less exposure to data collection. However, I’m eager to learn! I’ll message you for more details.
Hello! It's great to see your enthusiasm for pursuing a remote research assistant position in data science, especially as a new Master's student. Your background in quantitative trading and recommendation systems provides a solid foundation, and your desire to explore applications in diverse fields like climate change, environmental studies, and pandemics highlights your versatility and willingness to learn. I encourage you to leverage online platforms, such as LinkedIn, ResearchGate, and academic forums, to connect with researchers and professionals in your areas of interest. Crafting a compelling message that outlines your skills, relevant coursework, and specific interests can help you stand out. Additionally, consider reaching out to professors or professionals whose work aligns with your goals, as they might have ongoing projects or collaborations in need of assistance. Participating in data science competitions, hackathons, or contributing to open-source projects can also enhance your experience and showcase your capabilities. Networking within academic circles and attending virtual seminars can further expand your opportunities and help you build valuable connections in the field. Best of luck on your journey to deepen your knowledge and contribute to impactful research!
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