Tech & Quant Finance Research Analyst

Tech Aalto Pte ltd; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Tech Aalto Pte ltd in Singapore is seeking a motivated Research Analyst with CS background to research cutting-edge technology and quantitative models, and to automate internal research and back-office processes.

You will work with investment professionals to translate findings into technical solutions, backtest investment strategies using historical data, and develop algorithms in Python and C#.

Qualifications

• Bachelor’s degree in Computer Science or a related field.
• Up to 3 years of experience in technology research or quantitative finance.
• Proficiency in Python and C# for developing algorithms and automation scripts.
• Familiarity with quantitative trading strategies and backtesting frameworks.
• Strong communication skills to present findings to stakeholders.

Responsibilities

• Technology Research: Investigate and analyze emerging technologies in consumer and enterprise software to inform investment decisions.
• Automation & Implementation: Develop and implement automated solutions for internal research, portfolio management, and back-office operations to enhance efficiency.
• Quantitative Research: Conduct research on quantitative models, including statistical analysis and algorithm development.
• Backtesting Strategies: Design and backtest investment strategies using historical data to evaluate performance metrics such as returns, volatility, and risk-adjusted returns.
• Collaboration: Work closely with investment professionals to understand their needs and translate them into technical solutions.

Skills

Python

C#

Analytical thinking

Education

Bachelor’s degree in Computer Science or related field

Tools

Backtesting frameworks

Job description

Tech Aalto Pte ltd in Singapore is seeking a motivated Research Analyst with CS background to research cutting-edge technology and quantitative models, and to automate internal research and back-office processes.

You will work with investment professionals to translate findings into technical solutions, backtest investment strategies using historical data, and develop algorithms in Python and C#.