Resume

Professional summary

I combine water-domain knowledge with software engineering to build internal platforms, SDKs, APIs, simulation workflows, and decision-support tools for infrastructure teams. Several are now in daily use across teams. Recent work spans digital-twin concepts for drinking-water treatment and distribution, internal Python SDKs adopted across a growing data team, governed adoption of generative AI, and PHREEQC/EPANET-oriented simulation workflows. I also coach engineers and help data teams turn prototypes into software they can support.

Selected systems & capabilities

Technical skills

Professional experience

Data Scientist: Applied AI, Internal Software & Data Platforms

Dunea N.V.

Jun 2021 to Present

• Develop digital-twin concepts for drinking-water treatment and distribution, translating telemetry, lab context, scenarios, replay, reporting, and validation needs into inspectable software workflows
• Create and maintain internal Python SDKs that standardize data access, wrap APIs, and encode reusable domain logic, now a shared foundation adopted across a growing data team for analytics, automation, and internal tools
• Build internal applications and services with FastAPI, React/Next.js, TypeScript, SQL, Azure services, Docker, CI/CD, authentication patterns, documentation, and Power BI where operational reporting fits
• Work on Python-based integration patterns for domain solvers such as PHREEQC and EPANET, connecting scientific models to web-based scenario and decision-support workflows
• Turn ambiguous, cross-team operational questions into data products that make assumptions, data quality, and decisions visible. Several are now in daily use across teams and credited with meaningful time savings, including work delivered in-house instead of outsourced
• Help mature data-science delivery practices through code review, typed interfaces, modular project structure, documentation, deployment discipline, Agile working methods, and handoff paths to managed platforms
• Shape governed AI adoption through early LLM experimentation, multidisciplinary exploration, ChatGPT/Copilot pilots, management briefings, responsible-use input, and AI-assisted engineering patterns
• Coach junior data scientists and data professionals, contribute heavily to recruiting and onboarding as the data team grew, and act as a practical bridge between domain experts, data-platform teams, software delivery, and leadership

Data Scientist

Crunch Analytics

Aug 2019 to Jun 2021

• Developed ETL pipelines, dashboards, and machine-learning models for clients in horticulture and retail
• Worked directly with clients to understand operational needs, scope projects, and deliver usable analytics solutions
• Automated data workflows with Python, SQL, and Power BI
• Took part in proposal writing, workshops, and recruitment efforts alongside a small, agile team

Student Assistant

Delft University of Technology

Sep 2016 to Jan 2020

• Supported course development by filming lectures, editing video, and building MOOC content
• Graded assignments and exams, created promotional materials, and helped organize faculty events
• Learned from working with dedicated researchers and students in a high-paced academic environment

Education

MSc Water Management

Delft University of Technology · 2016 – 2019

• Specializations: Water Resource Management, Hydrology

• Thesis: Investigating the MetOp ASCAT vegetation parameters with clustering

• Multidisciplinary project: Testing mobile data gathering in the Phetchaburi river basin and possible applications

Field experience

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BSc Civil Engineering

Delft University of Technology · 2011 – 2016

• Thesis: Improving water treatment processes at PDAM Tirtawening Kota Bandung

For our thesis, we travelled to Bandung, Indonesia, to improve the water treatment process at PDAM Tirtawening. We discovered that performance issues weren't due to one major fault but many small ones, like broken metering equipment and poor coagulant dosing. By introducing a few simple changes, we reduced turbidity by over 60%. The real fix wasn't expensive equipment, but better understanding and maintenance. Presenting our findings to the plant's director was a proud and eye-opening moment.

Field experience

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