Experience

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  University of california, santa barbara

  Jun 2011 - Sept 2011

  Visiting scientist

  Designed and managed two research projects supervised by Pr. J.W.Schooler on human attention. Led to two publications (2013, 2017).

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  École normale supérieure

  Feb 2012 - Sept 2015

  Chercheur

  - Led research projects on human attention- Programmed experiments in Python and MATLAB.- Analyzed data with R- Wrote and published articles in peer-reviewed journals- Presented results in international conferences- Supervised three master students- Developed the research app "Daydreaming" on Android

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  Université françois rabelais de tours

  Jan 2016 - Jul 2016

  University teacher - researcher

  - Teaching psychology, linguistics, research methods and statistics. - Managing and publishing behavioral and clinical research projects.

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  Qlip bv - quality assurance in dairy

  Oct 2017 - Sept 2019

  Data scientist innovation and business development

  ✔ Project management:- Leader of innovative projects in the dairy sector: conception, planning, development, implementation, and after-sales service. ✔ Chemometrics:- Development, validation, and maintenance of chemometric models using experimental designs in vibrational spectroscopy✔ Big data:- Development of big data models using millions of records out of administrative, veterinarian, economical, geographical, weather-related and expert sources of information. ✔ Data Science:- Development of real-time indexes using time series and text mining in the context of dairy. Show less

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  Crv

  Sept 2019 - Oct 2020

  Data scientist innovation

  ✔ Machine learning engineering✔ Data governance✔ (Data) Product management -> Customer research: define the right questions to answer -> Business strategy: make sure to make benefits out of the data science investment -> Agile project management: envision, plan, lead, execute, organize pilots, monitor, report, iterate.

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  Forfarmers

  Nov 2020 - now

  Senior data scientist

  Led all data science efforts at ForFarmers in the past 4 years.Year 1-2: setting up the requirements for professional data science in Azure. Testing Azure with ambitious machine learning Proof-of-Concepts (POC), as a product manager and data scientist. Lots of statistical (eg. linear mixed models) work too.Year 3-4: focusing on the implementation, growth and monitoring of the most promising POC machine learning solutions. Developing a data strategy mixing self-service analytics and support, mentoring, raising data literacy and awareness, and scouting high impact opportunities. Still lots of statistical analyses. What✔ Machine learning engineering (Pyspark Databricks, Azure Machine Learning, PowerBI)✔ Statistical expertise, data mining, process monitoring (R)✔ Product management -> customer and process optimization data products -> feasibility study, development, proof of concept, piloting of MVP, fully automated and scalable implementation How✔DevOps✔Stakeholder management ✔Mentoring colleagues and students Show less