Quantitative Researcher - Macro Trends

The role

• You will conduct original alpha research on global macro trends, developing and testing predictive signals to inform asset trading strategies.
• You will work across the entire research cycle—from hypothesis generation and statistical modeling through to implementation and ongoing performance review—with strong ties to fundamental economics and quantitative research.
• This is an exciting opportunity for someone who excels at combining economic insights with technical expertise and can help research and strategy teams achieve their goals.

Day-to-day responsibilities

• Research and develop alpha signals across global macro asset classes, with a focus on asset trends and directional performance.
• Model the relationships between macroeconomic events (e.g., earnings, monetary policy) across asset classes and identify patterns.
• Design and evaluate predictive signals using rigorous statistical and quantification methods.
• Collaborate on portfolio construction and risk analysis within the strategic strategies.
• Monitor the strategy's performance and translate economic signals into actual macro trade ideas.
• Collaborate with research teams (IR) and Data Science, and contribute to the broader research agenda.

Technical and Business Skills

• 2+ years of experience researching macro signals in the field of alpha research.
• Solid experience in statistical and mathematical modeling, using either classical or discrete methods.
• Strong quantitative skills, with experience in understanding and evaluating signaling systems across asset classes.
• Understanding of portfolio construction and risk analysis.
• Familiarity with alternative data and their integration into other quantitative risk models.

Personal Attributes

• At least 2 years of experience in institutional investing, equity research, or a corporate finance role.
• Strong ability to interpret qualitative, quantitative, and empirical data, with exceptional analytical thinking.
• You must have a bachelor's degree (or equivalent) in a quantitative discipline (e.g., mathematics, statistics, physics, computer science, engineering, econometrics) from a leading global university. Preference is given to candidates with a master's degree or Ph.D. in a related field.
• Solid database-driven and strong algorithmic development skills (SQL, Python, R, SAS, C#, Java, etc.), experience with data analytics tools, machine learning models (MLP, ANN, or other types), and data science applications.
• Exceptional communication and presentation skills, with the ability to explain complex concepts clearly and concisely.
• A strong attention to detail and a flexible approach. You have experience working effectively on your own or with some support from others to complete tasks quickly and accurately within tight deadlines.
• A commitment to continuous improvement and a passion for your field—always looking for ways to improve the accuracy and effectiveness of the methods you use. You are also detail-oriented and open to discussing your work with colleagues and mentors to identify areas for improvement.
• Ambitious and curious, with a drive to learn new technologies and approaches. Our team takes a highly collaborative and agile approach to business; we want our peers to proactively develop strategic initiatives to identify and act on new opportunities, and to take responsibility for their own development by continuously learning and applying new skills to their work.

Inclusion, Work-Life Balance, and Benefits

• For us, working at Mac means more than just providing job opportunities for everyone. Our inclusive environment prioritizes respect, supports personal development, and fosters innovation.
• To ensure our colleagues feel valued, we encourage curiosity and foster a friendly environment where everyone can be their true selves at work. A diverse, open-minded team is a great team.
• Through our wellness and well-being initiatives, learning and development, our learning platform, our learning and development, our learning and development, our learning platform, our learning and development, our learning platform, our learning and development, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform, our learning platform,