Southern Ridges Capital is an investment firm managing fixed income, currency assets, and derivatives by employing discretionary macro and relative value investment strategies.
We believe in cultivating a strong, collaborative culture where people are empowered to learn, grow, and do their best work. We are committed to mentoring early-career professionals and giving them the tools, exposure, and guidance to succeed in a dynamic and intellectually challenging environment.

TECHNICAL SKILLS

• A minimum degree with a major in data science, statistics, mathematics, physics, engineering, operational research, or a related field
• Proficient in Python and/or RA strong foundation in statistics, quantitative analysis, or data modeling

HELPFUL EXPERIENCE

• Exposure to macroeconomic or financial data tools like Bloomberg, CEIC, Haver, or Macrobond
• Interest in financial markets and macroeconomic trendsBasic understanding of options, derivatives, or econometrics

SOFT SKILLS

• A curious, analytical mindset and eagerness to learn
• Strong attention to detail and problem-solving skills
• Clear communication and willingness to ask questionsA team player who thrives in a collaborative and respectful environment

As a Quantitative Research Analyst, you’ll work closely with our investment team to develop insights and tools that directly support real-time investment decisions. This is a hands-on, learning-intensive role ideal for someone curious about financial markets and passionate about applying data-driven methods to solve complex problems.

Your key responsibilities will include:

• Conduct research and analyses on market and economic data
• Work with large data sets to identify, predict, and test market patterns
• Back-test and implement trading models and signals in a live trading environment
• Develop robust trading, risk analytics, and stress-testing frameworks/models

• Improve existing models, and translate algorithms into production-ready codeContribute to internal platform that present analytics developments in an accessible format