Quantamental Research Analyst

P2P; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

A financial research firm in Singapore is looking for a Quantamental Research Analyst to conduct in-depth research on ETF pricing and trading strategies. This role involves collaboration with traders and quantitative developers, analyzing corporate actions, improving dividend predictions, and using Python to handle large datasets. Candidates should have a Bachelor's degree in Finance, Economics, or Mathematics, along with 3–6 years in relevant research roles and a strong quantitative mindset.

Qualifications

• 3–6 years in buy/sell-side research, prop trading, ETF/index research, or corporate actions analysis.
• Experience dealing with large datasets using Python.

Responsibilities

• Collaborate with quantitative traders in research on ETF pricing and trading strategy.
• Analyze corporate actions and fair value to generate trade ideas.
• Improve dividend predictions and understand their impact.
• Work with equity quants on datasets and prediction models.
• Identify trading opportunities from macroeconomic events.

Skills

Attention to detail

Quantitative mindset

Understanding of financial ratios

Python programming

Education

Bachelor's in Finance, Economics, Mathematics, or a related field

Job description

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models. We are looking for a Quantamental Research Analyst with a passion for financial markets and a solid understanding on company fundamentals, who possesses a quantitative mindset to join our team in Singapore.

What You'll Do:

• Collaborate with quantitative traders globally in performing in depth research on ETF pricing and trading strategy
• Analyze the fundamental implications of corporate actions and special situations; determine fair value and generate trade ideas
• Improve dividend predictions and analyze their impact on equity indices and futures.
• Work with equity quants to study internal and external datasets, understand their relationships with asset prices, and develop prediction models or actionable use cases
• Work with quantitative developers to productionize, automate, and scale research and trading processes
• Be on top of macroeconomic events and market news in identifying the potential trading opportunities that is hard to capture through our automated strategies
• Other duties as assigned or needed

Skills You’ll Need:

• Bachelor’s in Finance, Economics, Mathematics, or a related quantitative field
• 3–6 years in buy/sell-side research, prop trading, ETF/index research, or corporate actions analysis
• High attention to details and apply to identify information that market might have missed
• Have the quantitative mindset to develop a systematic approach to address problems
• Good understanding of company fundamentals and financial ratios
• Comfortable to deal with large datasets using Python
• Desire to work within a collaborative, team-driven, fast‑paced environment