
Market News Event Analysis Intern
Position: Market News Event Analysis Model Intern
Location: Remote
Type: Unpaid Internship (Potential for future paid role)
Company: Swing Phi – Fintech | Economic Research & Market Intelligence
About Swing Phi
Swing Phi is an AI-powered fintech platform delivering real-time market research and economic intelligence to institutional and retail investors. We use data science, automation, and macroeconomic analysis to simplify complex financial decisions and bring clarity to markets.
About the Role
We’re looking for a Market News Event Analysis Model Intern to support the development of systems that detect and interpret market-moving news using machine learning and natural language processing. You’ll work closely with our engineering and research teams to build tools that turn unstructured news into structured, actionable signals.
This role is ideal for students with a computer science or data science background who want to apply NLP and event detection to real-time market analytics.
What You’ll Do
- Build and refine NLP models to extract entities, sentiment, and event types from financial news
- Engineer features from unstructured headlines and article content for downstream models
- Develop and evaluate classifiers that tag events by relevance, sector, and market impact
- Integrate external APIs (e.g., news, financial data) into model pipelines
- Help maintain labeled datasets for training and validation
- Collaborate on real-time alert systems that surface significant market news to users
Qualifications
- Pursuing a degree in Computer Science, Data Science, or a related field (junior/senior preferred)
- Strong experience with Python and libraries such as Pandas, scikit-learn, and spaCy or NLTK
- Understanding of NLP tasks such as named entity recognition, sentiment analysis, and text classification
- Interest in financial markets and real-time data applications
- Bonus: Familiarity with news APIs (e.g., NewsAPI, GNews), vector embeddings, or LLMs
What You’ll Gain
- Hands-on experience building production-level NLP models in a fintech environment
- Opportunity to contribute to real-time systems that interpret news and influence investment decisions
- Exposure to live event-driven modeling and the intersection of AI, media, and markets