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    Senior Data Scientist - Toronto, Canada - Altus Group

    Altus Group
    Altus Group Toronto, Canada

    2 days ago

    Default job background
    Temps plein
    Description

    Catégorie d'emploi:

    Technologie

    Gamme des niveaux de rémunération :

    $66, $155,405.00

    Clause de non-responsabilité : L'échelle salariale de base représente les tranches inférieure et supérieure de la « gamme des niveaux de rémunération » du groupe Altus pour ce poste dans le lieu de travail principal. Les salaires d'embauche réels varieront en fonction de facteurs, y compris, mais sans s'y limiter, le lieu de travail, l'expérience et la performance. La fourchette salariale indiquée ci-dessus ne reflète pas la rémunération totale des employés du Groupe Altus. D'autres récompenses peuvent inclure une prime annuelle, des modalités de travail flexibles et de nombreux avantages spécifiques à la région.

    Débloquez votre expérience Altus

    Si vous cherchez à faire progresser votre carrière dans les domaines de l'analyse des données, de l'expertise et de la technologie pour le marché mondiale de l'immobilier commercial (CRE) en croissance rapide, il n'y a pas de meilleur endroit que le Groupe Altus. Chez Altus, notre travail est utile. Chaque jour, nos employés ont un impact, innovent et façonnent l'industrie mondiale de l'immobilier commercial et de la PropTech.

    Notre culture centrée sur les personnes vous permet d'agir dans un climat de confiance et de performance, au sein d'une équipe inclusive qui collabore à la modernisation de notre secteur d'activité. Nous investissons dans nos collaborateurs en leur proposant des formations et des opportunités de croissance conçues pour les faire progresser dans leur carrière, tout en leur offrant un lieu de travail flexible et progressif qui reflète nos valeurs et nos équipes.

    The Data Scientist will work as part of the Altus Group R&D organization to build data science and machine learning solutions for commercial real estate (CRE). At Altus Group, Data Scientists have access to unique talent and data to build new models as part of a growing team. Data and analytics will help to shape the future of property technology and commercial real estate. Data Scientists collaborate with engineers and data architects to integrate their models into pipelines for internal and client consumption. Successful Data Scientists build analytics and machine learning solutions that create outsized investment performance for CRE clients.

    Key Responsibilities:

  • As part of a data team, design, build and improve Altus Group data science and machine learning models
  • Collaborate with R&D resources to define and scope data science solutions
  • Manipulate and clean data (exploratory data analysis), build new features (feature engineering), perform feature selection and model selection, and implement production-ready models
  • Participate in model and code reviews and contribute to a team consistently shipping new or updated analytics solutions
  • Define and implement metrics that will track model performance over time to identify risks and opportunities
  • Communicate results and insights from data science initiatives to stakeholders and other internal/external users and customers

    • Key Qualifications:

  • A scientist at heart. You are thoughtful and rigorous about modeling methodology and setting standards for exploration and experimentation. You creatively apply existing methodology to new analytical challenges and thrive on asking "What if?" questions.
  • Skilled in statistics/machine learning. You have applied experience with statistics/machine learning. Python toolkits you may have used recently include statsmodels, scikit-learn, or tensorflow.
  • You have demonstrated programming expertise with Python and SQL for ML techniques, including feature engineering/selection, model selection, model tuning, and performance measurement.
  • 2+ years of experience working in an applied data or analytics position, depending on academic background
  • Demonstrated accomplishments in data science or analytics, including: Data wrangling: transformation and cleaning, Feature engineering, Statistical or ML model implementation
  • Experience with data engineering and/or collaborating with data engineers
  • BS or MS degree in Statistics, Data Science, Economics, Computer Science, or a related technical field

    • Ce que le Groupe Altus offre :

  • Récompenser les performances : Nous sommes heureux de pouvoir offrir à nos employés une rémunération compétitive, des plans d'incitation et de primes, ainsi qu'un ensemble de récompenses qui donne la priorité à leur santé mentale, physique et financière globale.
  • Croissance et développement : En tant que destination pour les meilleurs talents de l'industrie, nous investissons en vous pour répondre aux besoins changeants de nos clients et atteindre vos objectifs professionnels. Notre Altus Intelligence Academy offre plus de heures de matériel d'apprentissage pour répondre aux différentes étapes de la carrière d'un employé.
  • Modèle de travail flexible : Nous modernisons nos programmes pour les employés afin de refléter le nouveau monde du travail. Notre modèle de travail basé sur l'activité vous offre la flexibilité d'aligner votre lieu de travail sur le travail effectué - le bureau pour la connexion et la collaboration, et l'éloignement pour le travail ciblé.

    • Le Groupe Altus s'engage à favoriser un environnement de travail inclusif où tous les clients et employés se sentent accueillis, acceptés et valorisés. Nous offrons une atmosphère sans barrières pour promouvoir la diversité, l'équité et l'inclusion, et encourageons l'égalité des chances pour tous les employés. Nous recherchons des candidats ayant des expériences diverses et offrons des expériences accessibles aux candidats tout au long du processus de sélection. Si vous avez besoin de mesures d'adaptation, veuillez nous contacter à l'adresse ou au

    Nous apprécions tous les candidats qui prennent le temps de postuler au Groupe Altus. Veuillez noter que seules les personnes sélectionnées pour poursuivre le processus seront contactées. Nous vous remercions de votre attention.

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