Professional Experience

Research Data Scientist - Churned AI (2021-2022)

• Research & Development: building the Churned Analytics Engine that automatically performs estimation and testing of econometric and machine learning models on data provided by various companies with a subscription-based revenue model

• Researching the optimal theoretical modelling strategies for churn data 

• Developing a Python package that is integrated into the dashboard of the client company, providing real-time insights into their customer churn rates that is still in use today

Data Science Work Student - Logex Healthcare Analytics (2018-2019)

• Part of the Clinical Outcomes Benchmark team that creates performance reports of medical specialists of 90% of Dutch hospitals

• Composed the draft version of performance reports for the first foreign hospital client, including data cleaning and preparation

• Designed helpful benchmark insight report for the analyst team, containing the status of data delivery of all hospitals 

• Created insight reports of surgery times and registration practices of surgeons across Dutch hospitals on request of the Dutch National Healthcare Authority (NZA).

Bachelor Thesis Intern - Accenture (2018) 

• Individual consultancy project: forecasting the sales for fan shop of a Dutch premier league football club in the Netherlands in combination with Bachelor thesis about Vector Auto Regressive (VAR) modelling

Education

PhD Candidate Econometrics & Data Science – Vrije Universiteit Amsterdam (2020-2025)                                   

• Affiliation to Tinbergen Institute, research institute in economics, econometrics and finance

• Research: Theoretical developments for causal inference with experimental and observational data, time varying structural parameter models, synthetic control methods

• Teaching: Advanced Econometrics (Msc. Econometrics), Business Statistics (Bsc. IBA), Supervisor of Msc. and Bsc. theses.

• Training includes Deep Learning Course (Neural Networks) 

Master of Science –Vrije Universiteit Amsterdam (2019 - 2020)

• Msc. Econometric Theory 

• Cum Laude (GP A: 8.4/10) and completed Honours Programme

• Courses include Time Series Analysis, Advanced Econometrics, Data Mining Techniques

Bachelor of Science - Maastricht University (2015-2018)

• BSc. Econometrics & Operations Research

• Cum Laude (GPA: 8.3/10) and completed Honours Programme

• Exchange semester to Hong Kong University of Science and Technology (HKUST)

Skills

Languages: English (fluent), Dutch (native), French (intermediate), Spanish (pre-intermediate)

Technical skills: Python (incl. object oriented), R, SQL, Matlab, LaTeX, MS Excel (VBA), Git