Data Scientist Intermédiaire (Python, Databricks, Spark, Ml), Institution Financière, Montréal (Hybr
Abbeal
Data Scientist intermédiaire (Python, Databricks, Spark, ML), institution financière, Montréal (hybride)
Concevoir des modèles de machine learning et d'analytique prédictive qui aident une institution financière canadienne à décider. Montréal, hybride 3 jours sur site, bilingue.Abbeal recherche un ou une data scientist de niveau intermédiaire pour une institution financière canadienne, à Montréal.L'équipe données et IA développe des solutions de machine learning qui éclairent les décisions d'affaires, en lien étroit avec les data engineers et les AI engineers qui les mettent en production.Le rôle
Modélisation statistique et analytique prédictiveExpérimentation : tests A/B et inférence causaleFeature engineering, évaluation et interprétabilité des modèlesMise en production avec les data engineers et AI engineersData storytelling et recommandations prescriptives pour les équipes métierProfil recherché
Au moins 3 ans en data science, formation quantitative (bac, maîtrise ou doctorat)Python et SQL (pandas, NumPy, scikit-learn)Git et Azure DevOps ou JiraPower BI ou TableauModalités
Montréal, hybride : 3 jours sur site, 2 jours en télétravailFrançais et anglais maîtrisésData Scientist intermédiaire (Python, Databricks, Spark, ML), institution financière, Montréal (hybride)
#J-18808-Ljbffr
Concevoir des modèles de machine learning et d'analytique prédictive qui aident une institution financière canadienne à décider. Montréal, hybride 3 jours sur site, bilingue.Abbeal recherche un ou une data scientist de niveau intermédiaire pour une institution financière canadienne, à Montréal.L'équipe données et IA développe des solutions de machine learning qui éclairent les décisions d'affaires, en lien étroit avec les data engineers et les AI engineers qui les mettent en production.Le rôle
Modélisation statistique et analytique prédictiveExpérimentation : tests A/B et inférence causaleFeature engineering, évaluation et interprétabilité des modèlesMise en production avec les data engineers et AI engineersData storytelling et recommandations prescriptives pour les équipes métierProfil recherché
Au moins 3 ans en data science, formation quantitative (bac, maîtrise ou doctorat)Python et SQL (pandas, NumPy, scikit-learn)Git et Azure DevOps ou JiraPower BI ou TableauModalités
Montréal, hybride : 3 jours sur site, 2 jours en télétravailFrançais et anglais maîtrisésData Scientist intermédiaire (Python, Databricks, Spark, ML), institution financière, Montréal (hybride)
#J-18808-Ljbffr
Vacancy posted 2 hours ago
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