Albert Lin
Class of 2027
Contact
- Email: ahlin3@andrew.cmu.edu
In This Section
- Academics
- Admissions
- Careers
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News
- 2025 MSCF Trading Competition
- A New Academic Year at MSCF
- Alumni Reflect on the MSCF Program鈥檚 30th Anniversary
- Breaking Barriers, Building Leaders: Women in Quant Finance
- Data Science in Finance
- Financial Engineering Salary
- High Stakes and Fair Values: 91视频 Students Face Off in the 2026 Market Making Game
- How to Become a Quant
- MSCF 30th Anniversary Celebration
- MSCF Advisory Board Member, Roni Israelov receives the 2024 Peter L. Bernstein Award
- MSCF Hosts 2025 Panel for Women in Data Science Pittsburgh
- MSCF Hosts 2nd Annual Datathon: Advancing Experiential Learning and Industry Connections
- MSCF Welcomes Rhonda Khan as Communication and Leadership Instructor and Coach
- MSCF Welcomes Shelli Faber as Associate Director of Career Services
- Quantbot Classroom Naming
- Squarepoint Foundation Deepens Partnership MSCF Through $100K Gift to Support Future Leaders
- Our Community
- Student Experience
Biography
"Information is the resolution of uncertainty." - Claude Shannon
This principle guides Albert Lin's approach to quantitative research: reduce market uncertainty through sharp observations, rigorous analysis, and smart modelling.
Albert Lin holds a dual bachelor's degree in BS Computer Science and BBA Finance from National Taiwan University. His strong academic foundation, combined with deep curiosity about financial markets, has led him to three internships and one full-time role in trading firms.
At Kronos Research, Albert worked on high-frequency trading strategies with C++, focusing on strategy refinements and trading decisions, during his internship. In his full-time role, he contributed to cryptocurrency HFT alpha research by applying machine learning and deep learning models for HFT alphas and return prediction. Prior to this, he interned at WorldQuant, focusing on systematic US equity alpha research and backtesting. His earlier experience at Jim Quant Capital involved developing unsupervised stock clustering and pair trading strategies, further enriching his understanding of diverse market structures.
Albert is currently seeking a buy-side quantitative researcher or trader position. He brings a blend of theoretical rigor and hands-on experience, with particular strengths in machine learning, mathematical acumen, and production-grade implementation. His multidisciplinary background and collaborative mindset make him a valuable asset to any research-driven team. He is available to connect virtually or in person to discuss how he can contribute to your team's success.
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