Quantitative Analyst / Researcher (Entry-Level)

Role overview

This entry-level role is centered on quantitative analysis and research, helping teams build data-led models, analytical methods, and research outputs that support better business decisions. The work blends mathematics, statistics, programming, and problem-solving to uncover patterns, test assumptions, and turn complex data into practical insights.

What you will do

• Gather, prepare, and analyze large datasets from a range of structured and unstructured sources.
• Use statistical techniques and quantitative methods to examine relationships in data and assess hypotheses.
• Support the creation, testing, and improvement of mathematical and statistical models.
• Review model performance, run backtests, interpret outcomes, and suggest refinements to improve reliability and predictive strength.
• Carry out research tasks such as literature reviews, market scanning, industry trend analysis, and dataset exploration.
• Convert findings into reports, presentations, and recommendations that aid planning and decision-making.
• Work with analysts, researchers, engineers, and business stakeholders to clarify goals and deliver analytical solutions.
• Assist with dashboards, visualizations, and automated reporting tools that make insights easier to understand.

What the role calls for

• A solid grasp of mathematics, statistics, probability, and quantitative reasoning.
• Comfort using Microsoft Excel for spreadsheet-based analysis.
• Exposure to Python, R, SQL, or similar tools used for analytics and data work.
• Ability to collect, clean, structure, and interpret large volumes of data.
• Strong critical thinking, analytical judgment, and problem-solving ability.
• Understanding of statistical modeling, hypothesis testing, and data interpretation.
• Capability to research information from multiple sources and assess its relevance.
• High attention to detail and a strong focus on data accuracy.
• Clear written and verbal communication, including the ability to explain findings well.
• Useful familiarity with data visualization and reporting tools.
• Good organization and time management.
• Ability to work both independently and as part of a collaborative team.
• Interest in research, forecasting, optimization, analytics, and data-driven decision-making.

Additional notes

This position is described as entry-level and is based onsite in Australia. A strong sense of curiosity, adaptability, and a willingness to learn new quantitative methods and technologies are important for success. The role contributes to innovation, forecasting, optimization, and evidence-based decision-making through rigorous analysis and research.