Description

You will build and scale technology platforms to support quantitative research and analytics for investment decision-making.

Responsibilities

• Develop code libraries and solutions to augment existing structures for research-driven investment processes.
• Build large-scale distributed computing programs to generate analytics and user-friendly visualizations.
• Lead the transition of matured prototypes and interim tools into production environments.
• Implement standards and tools for numerical library testing, code quality controls, and requirement verification.
• Partner with product owners and quantitative teams to implement models and improve proprietary algorithms.

Required Skills

• 12+ years of progressive experience in software engineering and quantitative analysis.
• Expert proficiency in Python and PySpark.
• Advanced knowledge of R and Java.
• Hands-on experience with PySpark, Pandas, Polars, and Cuml.
• Strong experience with large datasets and big data cloud platforms like Databricks.
• Deep understanding of algorithms, data structures, and Test-Driven Development.
• Advanced mathematical knowledge in statistics, time-series analysis, and asset pricing theory.
• Solid understanding of tradable financial instruments, including securities and derivatives.
• Experience with real-time, batch, and orchestration architectures.

Preferred Skills

• Advanced degree in Computer Science, Math, or Financial Engineering.

Key Skills

Education

Any Gradute