Oxford, England, United Kingdom
— Developing quantitative models for trend forecasting, portfolio optimisation, and macroeconomic regime detection — Building scalable backend systems (Django REST, Python, PostgreSQL pipelines) with API endpoints powering financial model outputs — Architecting cloud infrastructure across AWS and GCP for secure, low-latency model delivery — Deploying cross front-end platforms including user-facing dashboards, watchlists, and interactive analytics — Managing data engineering and database development, integrating multiple data vendors and automating ingestion pipelines — Directing UI and UX to ensure user centric and behaviourally conscious interfaces and institutional-grade visualisation — Leading business development, fundraising, and partnerships including successful acceptances into AWS Activate and NVIDIA Inception programs — Overseeing corporate governance and compliance, from shareholding structures to legal filings and IP protection
— Quantifying interest rate risk and credit risk exposures of various financial institutions across Türkiye, Azerbaijan, and Serbia through EVE & NII Analyses and IFRS9 Impairments, respectively — Developing Machine Learning systems for institutional clients to capitalise on active fixed-income investment strategies and optimise trading books thereof through macroeconomic regime breaks
— Synthesising data and information on trends in global financial markets using Machine Learning models in Python — Developing predictive analytic models with high forecast accuracies to capture directional momentum on assets of interest — Overseeing investments in multi-asset portfolios at exchanges in New York, London, Frankfurt, and Tokyo (54% USD ROI in 2022) — Reviewing empirical finance literature to develop multi-strategy model portfolios for diversifying exposure to Germany & Japan — Advising households from various countries in Europe on their strategic and tactical investments and financial planning challenges — Writing internal newsletters and analyses on the global macro-financial architecture
— Carrying out extensive empirical research across asset management, debt markets, and corporate finance using Stata and Python — Reviewing papers for coherent empirical results before publication at top journals – i.e. Acharya et al. (2021), NYU Stern School of Business — Overseeing weekly lectures & exercise sessions for Corporate Finance & Risk Management courses
— Conducting literature review on changing panel composition and non-response in survey forecasts for the ZEW’s flagship Financial Market Survey — Developing econometric robustness tests on the panel data from the survey forecasters on German Economic Health Indicators to eliminate inherent biases using Python — Analysing systemic risk linkages between conventional financial markets and Decentralised Finance systems as part of a policy discussion project — Scrutinising the AML & CFT literature along with the construction of geospatial data and of Machine Learning models thereupon