Amsterdam, North Holland, Netherlands
Advanced analytics manager with 10+ years leading AI, ML and analytics initiatives, data strategy, and high-performing teams. Proven track record in delivering data-driven, production-ready solutions—from predictive models to intelligent automation—that enhance decision-making and streamline complex workflows. Combines strong technical expertise across data engineering, ML, and AI integration with effective stakeholder communication, bridging data teams and business leadership. Experienced in mentoring teams, and building enterprise-scale data-driven cultures.
Managed an analytics team of data scientists, analysts, and engineers, delivering predictive and prescriptive models—including forecasting and optimization solutions—to support business performance, and strategic decision-making. Responsible for defining the data science strategy and KPIs, identifying high-impact AI opportunities, and driving AI/ML adoption and automation. • Built and deployed forecasting, machine learning and optimization models for sales and cost planning, an advertisement and promotion model covering marketing campaign and spending, and self-service analytical tools and deep-dive dashboard • Drove AI and LLM integration across development and business processes such as introducing AI workflows, automated review pipelines, and LLM-based summarization, reducing manual effort and accelerating analytical output quality • Partnered with senior leadership to discuss data science outcomes and strategic roadmaps, translating complex models and technical findings into clear, actionable narratives for non-technical audiences • Defined and governed ML and AI architectures end-to-end, ensuring alignment with the broader data strategy • Mentored team members in model design, architecture, and engineering best practices; ran training sessions with business stakeholders to build ML literacy and embed data-driven thinking into day-to-day decisions
Led multiple client behavioral modeling projects under tight deadlines, managed stakeholder communication, planning, and resource allocation for cross-functional project teams and delivered solutions. Drove the adoption of data science best practices, modeling and coding frameworks, and a data-driven way of working across the teams. • Built, maintained and fine tuned models for client behavior, and capital allocation (e.g.economic capital), directly influencing investment decisions and product pricing • Led end-to-end integration and redevelopment of multiple fragmented client behavior and statistical models into a new unified predictive engine, creating a new Python-based back-end from scratch and delivering a user-friendly self-service front-end for internal users, significantly reducing runtime, maintenance overhead, and improving model explainability and adoption • Co-created a standardized coding and modeling framework and built custom Python modules adopted organization-wide, raising data science standards across the team • Mentored colleagues in data science and financial modeling, fostering knowledge sharing and best practices
Built the foundation for advanced analytics and client behavioral modeling within Treasury. Collaborated across departments and geographies to develop and implement a behavioral modeling framework and governance structure. Translated model results into product pricing, investment decisions and hedging strategies for the bank and communicated them to senior management. • Developed models covering ~100% of the mortgage portfolio to predict prepayment risk and repayment timing, and deposit behavior models across current and savings accounts (50%+ of the balance sheet) to estimate deposit stability/evolution, core balances, and interest rate sensitivity alongside customer segmentation and churn prediction models • Designed a behavioral modeling framework subsequently adopted across multiple subsidiaries • Built automated ETL pipelines from scratch, generating previously unavailable client behavioral insights from large-scale transactional data used for both predictive modeling and senior management reporting • Regularly presented model methodologies, results and strategic recommendations to senior management, directly influencing the bank’s investment and pricing decisions
• Mentored junior team members, providing guidance on both technical skills and professional development • Mentored junior team members, providing guidance on both technical skills and professional development
Led modeling, BI, and risk projects across business, trading, and asset-liability management functions, managing cross-functional project teams and rebuilding core pricing, behavioral, and reporting infrastructure. • Developed and deployed advanced pricing, forecasting, and behavioral models supporting trading and treasury operations • Built scalable data pipelines and interactive dashboards providing insights on risk metrics and portfolio performance • Regularly presented model results and business performance analyses to executive board, translating complex quantitative findings into clear strategic recommendations to support decision-making
Course: Financial products and financial processes (Msc) The objective of the course is to familiarize students with the financial markets' instruments, behavior market players and the operation of the markets. The core part of the course is the pricing and hedging of derivatives like options, futures and swaps. There are many real life calculation exercise during the course. Students need to use programming to solve the exercises and they also use Bloomberg in seminars to get familiar with products and market prices.
Gave lectures and seminars: -Modern Corporate Finance (BSc) -Financial Calculations and Financial Markets (BSc) -Investments (MSc)