Senior Data Scientist
il y a 1 mois
De data scientist zal bijdragen aan een rijtijd-analyseproject met als doel de stiptheid van voertuigen aanzienlijk te verbeteren.
Dit project is gebaseerd op big data analytics en vervangt de traditionele methode voor het bepalen van rijtijden, waarbij rijtijden per lijn werden aangepast, door een moderne big data aanpak. Bij het project gebruiken ze data van hun voorspellingsmodel van toekomstige rijtijden op basis van recente trends, met als doel de planning te optimaliseren.
De professional zal werken met Python en Apache Spark in Databricks om analyses uit te voeren op de voorspellingen van het huidige rijtijd-predictie model en zal dit model verder verbeteren, inclusief het optimaliseren van het (distributed) XGBoost-model. De focus van de data scientist ligt op het verbeteren van het predictie model door middel van feature engineering, het toevoegen van variabelen, het optimaliseren van regularisatie,.
Hierbij zal de professional de bestaande aanpak kritisch evalueren en de code grondig reviewen. Daarnaast kan de data scientist nog aan nieuwe voorspellingsprojecten werken indien voldoende vordering bij rijtijd-analyses, zoals het voorspellen van de beschikbaarheid van voertuigen en chauffeurs.
De taken omvatten o.a.:
- Het voorstellen van optimalere tijdsblokken, met zo min mogelijk toename van de totale rijtijd, op basis van uitgebreide analyses.
- Het kwantificeren van onproductieve rijtijden, waarbij systematisch te veel tijd wordt toegewezen.
- Het ontwikkelen van een nieuwe planningsstructuur voor de “mínimale layover” (op basis van de onzekerheid wanneer een voertuig aan de laatste halte toekomt).
- Het valideren van de voorspelde rijtijden ten opzichte van zowel de oude historische data als de werkelijke rijtijden.
Indien er aanzienlijke vooruitgangen zijn geboekt met eenvoudigere ML modellen (XGBoost, etc), kan de Data Scientist mee een geavanceerder distributed machine learning model (bijvoorbeeld een neuraal netwerk met attention) opzetten voor meervoudige en accuratere output (rijtijden, op
- en afstappers, etc ), rekening houdend met de run time en kost om het model te runnen.
Daarnaast zal de professional, samen met andere teamleden, de aanpak kritisch evalueren, code reviews uitvoeren, en gezamenlijk een statistisch rapport opstellen om de methodologie te documenteren, de resultaten te presenteren, en de huidige en toekomstige richting van het project te bespreken.
**Must have skills**:
- Min. 3 jaar ervaring met het ontwikkelen en valideren van machine learning-modellen in een productieve omgeving.
- Ervaring met het verwerken en analyseren van datasets, inclusief data cleaning.
- Kennis van datavisualisatietools zoals matplotlib, seaborn, of PowerBI,
- Ervaring met Apache Spark, Databricks, en gedistribueerde computing voor het verwerken van grote datasets.
- Ervaring met Python en machine learning-bibliotheken zoals scikit-learn, TensorFlow, of PyTorch.
- Aantoonbare expertise in gedistribueerde machine learning en het schalen van AI-modellen op grote datasets.
- Min. 5 jaar ervaring in het optimaliseren/tunen van databases en queries.
- Min. 5 jaar ervaring met het analyseren van datastromen.
- Ervaring met scripting (Shell, perl, python)
- Ervaring met databanken (SQL, Oracle)
- Taalvereiste: Nederlandstalig op Europees CEFR - niveau C2.
Locatie: Mechelen (hybride werkomgeving)
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