PROFILE

A highly accomplished macroeconomist and quantitative systems architect with over 17 years of experience in economic policy analysis, macroeconomic modelling, and financial risk analytics. Demonstrated expertise in designing and deploying advanced analytical systems that integrate econometrics, machine learning, and data engineering to support evidence-based policymaking and financial sector surveillance.

Currently serving in a senior leadership capacity, with a proven track record of directing multidisciplinary teams in the development of macroeconomic databases, automated statistical production systems, and central bank–grade forecasting and risk modelling frameworks across GDP, inflation, balance of payments, and labour statistics.

Specialised in the development and operationalisation of hybrid modelling frameworks, combining traditional econometric techniques (VAR, DSGE, panel models) with modern machine learning approaches, including factor-augmented models, anomaly detection systems, and AI-driven forecasting engines. Recently developed an integrated Financial Risk Surveillance Platform for banks and Financial Intelligence Units (FIUs), incorporating machine learning, rule-based AML systems, network analytics, and trade-based money laundering (TBML) indicators for real-time risk detection and prioritisation.

Technically proficient in Python, R, SQL, MATLAB, and EViews, with strong capabilities in data architecture design, automated data pipelines, dashboard development, and high-frequency data analytics. Extensive experience in managing large-scale economic and financial datasets, ensuring data integrity, and deploying scalable analytical tools for institutional use.

Recognised for advancing model governance, validation, and documentation standards, and for translating complex quantitative outputs into actionable insights for senior policymakers. Adept at stakeholder engagement, policy advisory, and capacity building, with a strong commitment to strengthening institutional analytics and supporting strategic decision-making under uncertainty.