Quantitative Researcher - Strategy

ADIC is seeking a Quantitative Researcher to join the Strategy team. The successful candidate will play a key role in supporting ADIC's investment process through quantitative research, model development, and AI-driven solutions.This role offers the opportunity to contribute to investment decision-making across both public and private markets by developing systematic signals, valuation models, and portfolio construction tools. The successful candidate will work closely with investment professionals across the Strategy team to enhance quantitative capabilities and support the development of innovative investment solutions.Key Responsibilities Generate and test alpha signals and factor ideas across asset classes using statistical and machine learning techniques. Conduct quantitative research and develop valuation models across both public and private markets. Design, backtest, and evaluate quantitative models, systematic strategies, and portfolio construction frameworks. Build and enhance risk models, performance attribution frameworks, and investment analytics. Develop end-to-end quantitative tools and applications to support investment workflows, from data ingestion through to deployment. Partner with investment professionals across the Strategy team to deliver research, model specifications, and quantitative insights. Drive AI and machine learning initiatives, identifying opportunities to enhance research and investment processes. RequirementsExperience Minimum 5 years of relevant experience in quantitative research, systematic investing, portfolio construction, asset allocation, or investment strategy. Experience conducting quantitative research across public markets, with exposure to private markets considered advantageous. Proven experience designing, backtesting, and implementing quantitative models or systematic investment strategies. Experience applying AI and machine learning techniques to financial datasets and developing production-ready analytical tools. Education Bachelor's degree in Finance, Mathematics, Engineering, Computer Science, Statistics, Physics, or another quantitative discipline. Master's degree or PhD is considered a strong advantage. Technical Skills & Knowledge Strong programming skills in Python or another object-oriented language, with experience developing production-quality code. Good understanding of quantitative modelling, time-series analysis, factor models, and portfolio optimisation. Experience with machine learning frameworks such as scikit-learn, TensorFlow or PyTorch. Knowledge of SQL, cloud platforms, and Git-based development practices. Strong understanding of financial markets, including equities, fixed income, private markets, and their application to portfolio management and asset allocation. Excellent analytical and communication skills, with the ability to present complex quantitative findings to investment stakeholders.