Looking for a new role as a AAA Global in United States, ? This Full-time position is perfect for professionals in the Investment Management and Financial Services sector. Gain hands-on experience in the Research, Engineering, and Finance department, where you’ll be at the forefront of exciting projects and innovation.
Why This Job Is Great for You:
- Employee Rating: Rated 3.8/5 by employees — get a sense of the company culture!
- Job Level: This role is ideal for professionals at the Entry level Level Job.
- Posted: Posted 15 hours ago, this role is still accepting applications. Act fast and apply today!
This opportunity offers valuable experience in the Research, Engineering, and Finance department and will help you advance your career in the dynamic world of Investment Management and Financial Services.
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“AAA Global” Company Job Details
- Company Name: AAA Global
- Work Type: Full-time
- Rating: 3.8 / 5
- Location: United States,
- Industry: Investment Management and Financial Services
- Department: Research, Engineering, and Finance
- Experience Level: Entry level
- Job Creation Duration: 15 hours ago
Job Details of Quant Researcher(Machine Learning)
We are seeking a talented Quant Researcher to help build the next generation of alpha signals in commodity futures. Our research is grounded in advanced machine learning, robust testing frameworks, and a deep understanding of global commodity markets.
Key Responsibilities
• Research, prototype, and validate systematic trading signals across commodities
using advanced ML methods.
• Design and implement rigorous backtests with realistic frictions, walk-forward
validation, and robust statistical tests.
• Engineer and evaluate novel features from prices, fundamentals, positioning,
options data, and alternative datasets (e.g., satellite, weather and global commodity
cash pricing).
• Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging
ensemble and Bayesian methods.
• Develop portfolio construction and optimization techniques and analysis tools to be
able to enhance performance and track effects on portfolio execution.
• Collaborate with developers to transition research into production-ready strategies.
Requirements
• Masters or PhD in either Statistics, Economics, Computer Science.
• Strong background in machine learning and statistical modelling (tree-based
models, regularization, time-series ML).
• Proficiency in Python (pandas, NumPy, scikit-learn, XGboost, PyTorch/TensorFlow).
• Understanding of time-series forecasting, cross-validation techniques, and avoiding
look-ahead bias.
• Academic experience in research and proven ability to translate academic work to
production code.