Data Lead
Engineering Systems
& Data.

I'm Ian, a data engineer from Amsterdam. Two loves have shaped most of my choices: languages and complex problems. The first has me at five languages and pulled me to Italy for part of my studies. The second became my work: taking a messy, real-world problem and building the system that answers it. Cities are my favourite version of that problem, which is why my research keeps returning to urban dynamics: how neighbourhoods change, when a metro line moves prices, what makes a place reachable.

My skillset: translating stakeholder requirements into sustainable business solutions that work.

Full CV below
Ian Ronk

Four competences, one constraint: a calibrated pipeline tends to outlast a clever one.

Data Engineering

Building and maintaining pipelines and efficient storage: three years of weekly collection across 8 authenticated sources at 300k records a week, with schema, orchestration and failure handling designed up front.

AirflowPythonETLMonitoringIceberg

Analytics & ML

The analysis layer on top: nowcasting on sparse official statistics, a monthly house-price index across 13 EU countries, regressions and hedonic pricing, and simulations such as agent-based gentrification models.

RegressionTime SeriesABM SimulationsApplied ML

System Architecture

The platform underneath: server instances, PostGIS, distributed Iceberg compute, networking/VPN, APIs and security. 13 different services run as production infrastructure.

Linux/BashNetworking & APIsDockerDistributed ComputeS3

Product Ownership

End-to-end ownership from method to shipped API: a 13-server build, client stakeholders from pension funds to statistics bureaus, and a team of 4–5 led at KR&A.

Team of 4–5StakeholdersRoadmapShipped APIs

Five years building
production data systems.

5+ years building and leading production data systems (pipelines, forecasting, geospatial) across European markets and academic research.

Download the CV (PDF)

Professional Experience

Head of Data
KR&A · Amsterdam · Jul 2025 – present
  • Lead a team of 4 through a transformation of the product offering, serving pension funds and leading FinTechs.
  • Develop, maintain and expand data pipelines (e.g. a weekly scrape of 300k records) and spatial big data products.
  • Delivered a global connectivity score: 1TB+ processed across 13 servers into a production API.
  • Represent the data function with clients: defending methodology against PhD-level scrutiny, presenting to portfolio managers and senior stakeholders.
  • Drive AI adoption: OCR and LLM document extraction, agentic pipeline monitoring, agent-assisted development.
Independent Researcher
urban dynamics · 2025 – present
  • Self-directed research programme: two working papers and a method paper in preparation (see Research), each backed by an open, reproducible pipeline.
Medior Data Scientist
KR&A · Jun 2022 – Jul 2025
  • Project lead for two multi-year projects, including a 3-year hedonic house-price-index project for Eurostat: scraping, storing and managing the data, building the regressions, interpreting results.
  • Restructured data infrastructure from legacy systems to Airflow, Iceberg and FastAPI.
  • Client-facing throughout, with CBS, Eurostat and pension funds.
Junior Data Scientist
KR&A · Oct 2021 – Jun 2022
  • Flood-occurrence prediction from alternative data (BSc-thesis project); 90%+ accuracy in risk classification.
  • Improved API efficiency tenfold through spatial optimisations, resulting in promotion.
Junior Full-Stack Developer
Exact (former SRXP) · part-time · Sep 2019 – Sep 2022
  • Enterprise expense-declaration software (EmberJS, PHP) under CI/CD and testing.
  • Maintained a client-facing webapp, working on business logic and styling.

Research Topics

Calibrating Free Postcode Boundaries from OpenStreetMap
Release August 2026

Seed-density-to-IoU calibration of an OSM-Voronoi pipeline; NL/DK references, transfer to BE, applied to Italy's 4,209 CAP polygons.

US vs EU: Does Training-Data Geography Matter for Autonomous-Driving Object Detection?
preprint

Controlled 2×3 fine-tuning study (YOLOv3/YOLOv8): US fine-tuning transfers roughly nothing to European streets (+0.001 vs +0.153 mAP in-domain).

Education

MSc Data Science & Business Analytics
Bocconi University · 107/110 · 2023 – 2025
Focus: Finance · Econometrics · Statistics · NLP
Thesis: Building an Agent-Based Model to Explain Gentrification in European Cities
BSc Artificial Intelligence
University of Amsterdam · 7.6/10 · 2019 – 2023
Minor in Linguistics, University of Amsterdam
Erasmus minor, Università di Bologna (UNIBO)

Stack

PythonSQLPostGISAirflowIcebergDuckDBDockerPyTorchBash

Languages & Soft Skills

Dutch C2 · English C2 · Italian B2/C1 · German B2 · Spanish A2

Multi-year project management · Client & stakeholder communication · Presenting and defending methodology to technical and senior audiences · Dependable

Resume & competences: Head of Data | Ian Ronk