Head of Data Science, Head of Risk Analytics, Director of Risk, Chief Data Officer, Quant Lead и Senior Director.

На данный момент Head of DS.

Мои компетенции и опыт

Over the past 15 years, I have led large-scale initiatives in Credit Risk, Data Science, and Advanced Analytics across leading financial institutions and international consulting projects. My primary focus has been on developing enterprise-level risk management frameworks, regulatory capital optimization, credit risk modeling, portfolio analytics, and building high-performing analytical teams.

My responsibilities included:

Leading cross-functional teams of data scientists, quantitative analysts, and risk experts (up to 100+ professionals).

Defining data and analytics strategy aligned with business and regulatory objectives.

Designing and implementing IRB/PD/LGD/EAD models, Expected Credit Loss (IFRS 9), stress testing, and capital optimization methodologies.

Developing portfolio monitoring systems, early warning indicators, and executive dashboards for senior management and boards.

Building model governance, validation, and monitoring frameworks in accordance with Basel II/III and regulatory requirements.

Driving the adoption of modern machine learning techniques, automated data pipelines, and cloud-based analytical platforms.

Managing interactions with executive committees, boards of directors, regulators, and external auditors.

Key achievements include:

Delivered large-scale regulatory capital optimization initiatives resulting in double-digit reductions in Risk-Weighted Assets (RWA).

Built and transformed independent model validation and model risk management functions from the ground up.

Developed advanced LGD and portfolio risk models that significantly improved capital efficiency while maintaining regulatory compliance.

Led enterprise-wide risk transformation programs involving data architecture, analytics platforms, and quantitative methodologies.

Successfully managed strategic projects involving international consulting firms and cross-functional business teams.

Established analytical governance processes that improved model quality, operational efficiency, and decision-making speed.

My work has been measured against business and regulatory KPIs, including:

Reduction of Risk-Weighted Assets (RWA).

Cost of Risk (CoR) optimization.

Regulatory compliance and successful model approvals.

Portfolio risk forecasting accuracy.

Model performance and stability metrics.

Delivery of strategic transformation programs on time and within budget.

Team development, stakeholder satisfaction, and successful implementation of enterprise analytics initiatives.

My technical expertise includes Python, SQL, PySpark, Spark, Hadoop, Hive, Airflow, MLflow, LightGBM, XGBoost, CatBoost, Power BI, and modern machine learning methodologies. I also have extensive experience with econometrics, causal inference, A/B testing, statistical modeling, and quantitative research.

I am particularly interested in senior leadership positions where I can combine strategy, quantitative analytics, data science, and business transformation to create measurable business impact.