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    Practice Lead Data Scientist, Data Driven Marketing - Montreal, Canada - Cogeco

    Cogeco
    Cogeco Montreal, Canada

    1 day ago

    Cogeco background
    Full time
    Description

    Our culture lifts you up—there is no ego in the way. Our common purpose? We all want to win for our customers. We aim to always be evolving, dynamic, and ambitious. We believe in the power of genuine connections. Each employee is a part of what makes us unique on the market: agile and dedicated.

    Time Type:

    Regular

    Job Description :

    SUMMARY

    As the Practice Lead within the Data Science and Analytics team at Cogeco, you will be at the forefront of our digital transformation efforts. Working closely with the team lead, your primary focus will be on driving strategic initiatives aimed at harnessing the full potential of Cogeco's data assets to enhance decision-making processes and spearhead the implementation of structured machine learning projects.

    Your responsibilities will extend beyond individual projects to encompass leadership of the practice, acting as a mentor to fellow Data Scientists and Analysts within the DDM team. Success in this role will require a balanced allocation of time between leading high-visibility projects and nurturing the professional growth of team members.

    In addition to mentoring, you will be instrumental in building and implementing models utilizing statistical approaches and algorithms. Your innovative thinking will be pivotal in proposing novel methodologies to deliver tangible business value.

    Join us in shaping the future of data-driven decision-making at Cogeco, where your expertise will drive impactful change and lead the way.

    PRINCIPAL RESPONSIBILITIES

    Strategic planning

  • Collaborate with stakeholders to define data science and analytical strategies and roadmaps that drive innovation by leveraging company data
  • Employ an iterative approach in the execution, regularly assessing progress, soliciting feedback from stakeholders, and adjusting plans as necessary to ensure alignment with evolving business needs and priorities.

    • Coaching and mentoring

  • Stay abreast of the latest advancements in data science, machine learning, and related technologies, and champion continuous learning and improvement within the team.
  • Coach and mentor team members by providing guidance on technical development and support shaping business acumen
  • Elevate the practice for the whole team

    • Data Analysis and communication

  • Analyze closely the data from the company databases to drive optimization and improvement of product development and business strategies.
  • Support our key stakeholders with analytics dashboard and analysis.
  • Communicate findings and insights effectively to both technical and non-technical stakeholders through presentations, reports, and data visualizations.

    • Technical Expertise and Model Development

  • Utilize LLM, advanced statistical and machine learning techniques to analyze complex data sets, develop predictive models, and derive actionable insights.
  • Develop custom data models and algorithms to deploy machine learning projects.
  • Use predictive modeling to increase and optimize customer experiences, revenue generation and customer retention.
  • Contribute to transformation projects to ensure the built models are incorporated into business processes.
  • Coordinate with different functional teams to implement models and monitor outcomes.
  • Develop processes and tools to monitor model performance and data accuracy.
  • Collaborate with cross-functional teams, including data engineers, software developers, and business analysts, to integrate data science solutions into operational workflows and systems

    • QUALIFICATIONS

    ACADEMIC TRAINING

  • Master in BI, Machine Learning, Data Science, Mathematics, Computer Science

    • WORK EXPERIENCE

  • 10+ years as leading a data function in industry

    • COMPETENCIES

  • Proven experience in leading data science projects
  • Strong communication skills and ability to translate technical concepts to non-technical stakeholders.
  • Understanding of underlying Machine Learning theory and the Predictive Modeling Life Cycle
  • Knowledge of data science frameworks: SQL, R, Python, Spark, Scala, or equivalent
  • Knowledge of machine learning libraries such as TensorFlow, Scikit-Learn, Pytorch or equivalent
  • Strong problem solving, time management and work organization skills.
  • Strong knowledge of mathematics, statistics and computer science necessary to build and deliver machine learning models.
  • Solid understanding of modern data infrastructure
  • Skills within Google Cloud Platform, Big Query (asset).
  • Ability to combine qualitative and quantitative insights
  • Strong business and product intuition
  • Understanding of broad spectrum of methods and disciplines in data science, and the applicability of different techniques for different contexts, e.g. not just focused on deep learning and predictive models
  • Constantly learning/growth mindset
  • Soft skills: leadership and communication

    • Location :

    Montréal, QC

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