Our Research Teams:
🏗️ Market Asset Analysis
📈 Macroeconomic Forecasting
🔬 AI & Data Science
- Build models to forecast liquidity needs under different scenarios (normal operations, stress, regulatory requirements).
- Support treasury, risk management, and strategic planning.
- Ensure compliance with local and international liquidity regulations (e.g., Basel III LCR/NSFR).
- Team Lead / Strategist: Defines vision, sets priorities, ensures alignment with long-term goals.
- Macro Analyst: Tracks global economic trends, FX, interest rates, and geopolitical risks.
- Sector Specialist: Focuses on industries (tech, energy, commodities, etc.) for deep insights.
- Quant/Data Analyst: Builds models, dashboards, and runs scenario simulations.
- Risk & Compliance Officer: Ensures adherence to regulatory frameworks and manages exposure.
- Operations & Documentation Manager: Maintains records, protocols, and training materials for generational transfer.
Chief Economist / Team Lead Sets vision, ensures alignment with policy or institutional goals, and communicates forecasts to stakeholders.
Macroeconomic Modelers Specialists in DSGE, VAR, and structural models; responsible for scenario building and stress testing.
Data Scientists & Statisticians Handle econometric analysis, machine learning forecasting, and big data integration (trade flows, sentiment, etc.).
Sectoral Analysts Cover key domains: fiscal policy, monetary policy, external sector, labor markets, commodities.
Financial Market Specialists Track FX, interest rates, capital flows, and link them to macro trends.
Research & Documentation Officers Ensure transparency, reproducibility, and clear communication of methodologies for internal and external audiences.
- Data Engineer: Builds and maintains data pipelines, ensures clean, reliable, and accessible data
- Data Scientist: Designs experiments, builds predictive models, and extracts insights from data.
- Machine Learning Engineer: Deploys, scales, and optimizes ML models in production environments.
- AI Researcher: Explores cutting-edge algorithms, deep learning architectures, and novel approaches.
- Business Analyst / Domain Expert: Bridges technical work with business needs, ensuring models solve real problems.
- Product Manager: Aligns AI initiatives with organizational goals, prioritizes projects, and manages stakeholders.
- MLOps/DevOps Specialist: Automates workflows, manages CI/CD for ML, monitors model performance.
- Data Governance & Ethics Lead: Ensures compliance, fairness, and responsible AI practices.