Job Description: Quantitative Research Intern -- Rates
Blockhouse's success stems from our groundbreaking approach to quantitative finance, blending sophisticated mathematical models with robust financial strategies to redefine market dynamics. We are seeking a Quantitative Research Intern -- Rates to transform raw data into predictive features that enhance trading strategies and execution models.
Key Responsibilities:
Feature Extraction and Signal Development
Design and develop informative signals with predictive power over financial variables, particularly in fixed income markets.
Analyze and transform complex datasets to generate features relevant for trading execution, liquidity risk monitoring, and market making.
Data Labeling and Weighting
Apply advanced techniques to label and weight data for feature generation.
Identify patterns in trading behavior, such as multi-leg trade execution (e.g., curve trades, basis trades, butterflies), and translate them into actionable features.
Classifier and Model Input Design
Use state-of-the-art methodologies to create classifiers and evaluate feature importance for predictive models.
Develop libraries of features that can be applied across multiple trading scenarios and asset classes.
Advanced Visualization
Create compelling visualizations to convey the insights and predictive power of engineered features to quantitative researchers and strategists.
Research and Innovation
Stay informed on the latest developments in information theory, signal extraction, and feature importance techniques, applying them to practical problems in quantitative finance.
Ideal Candidate Profile:
Educational Background
Currently pursuing or having completed a Bachelor’s, Master’s, or PhD in Computer Science, Financial Engineering, Mathematics, Data Science, or related quantitative fields.
Bachelor’s students with a strong willingness to learn and work hard are encouraged to apply.
Technical Expertise
Proficient in Python and familiar with libraries/tools for data processing and feature engineering.
Hands-on experience with machine learning frameworks and feature importance techniques.
Domain Knowledge
Strong understanding of fixed income markets and trading dynamics, particularly in relation to multi-leg trades.
Familiarity with transaction cost analysis and liquidity risk factors.
Analytical Skills
Exceptional problem-solving abilities and a detail-oriented approach to transforming data into meaningful features.
Communication and Collaboration
Capable of articulating complex ideas clearly and collaborating with quantitative researchers and strategists.
Why You Should Join Us:
Innovative Environment
Work with a forward-thinking team that leverages advanced feature engineering to drive innovation in quantitative finance.
Expert Team
Collaborate with top-tier talent in finance and technology, pushing the boundaries of predictive analytics and financial modeling.
Professional Growth
Develop expertise in feature engineering, signal extraction, and advanced visualization techniques.
Compensation
Equity-only compensation that reflects the value of your contributions.
Work Hours
A part-time role with 20-30 hours per week, offering flexibility and immediate start dates.
For International Students:
At Blockhouse, we value talent from across the globe and support international students through e-verification, CPT/OPT documentation, and flexible international payment arrangements.
If you’re passionate about transforming raw data into actionable insights and eager to apply your feature engineering skills to solve complex financial challenges, join us at Blockhouse and shape the future of finance.