Quantitative Developer

About Us: Scalar Field (https://www.scalarfield.io) is an early-stage startup backed by top-tier Silicon Valley venture capital firms. We're developing an innovative research platform that allows users to explore and back-test trading ideas. Our work involves tackling complex challenges in long-term planning to create a robust and sophisticated system.

Role: We're seeking a talented Quantitative Researcher to help develop our cutting-edge backtesting system. You'll apply advanced machine learning and AI techniques to create a platform that translates user queries into actionable trading research. A significant portion of your work will involve dealing with derivatives datasets.

Requirements:

• Solid understanding of derivatives and rates markets, including various derivative products, pricing models, and risk factors
• Strong background in machine learning and artificial intelligence.
• Excellent problem-solving skills and ability to tackle complex, multi-faceted challenges

Preferred Qualifications:

• Experience in solving problems related to long-term planning in AI systems
• Advanced understanding of derivatives pricing, hedging strategies, and risk management
• In-depth knowledge of interest rate markets, yield curves, and related financial instruments
• Understanding of financial market structures and trading mechanics

We Offer:

• Competitive salary and equity package
• Opportunity to work on cutting-edge problems in ML/AI while building a revolutionary product
• Collaboration with a world-class team of researchers and engineers
• Resources to continue learning and growing your expertise

If you're passionate about solving complex ML/AI challenges, have a strong background in derivatives and rates markets, and are excited about working extensively with derivatives datasets to make quantitative trading research accessible, we want to hear from you!