Principal Data Scientist

4 weeks ago

Montreal, Quebec, Canada Nurun inc. Full time

Position Overview:

The Principal Data Scientist plays a crucial role within Nurun, embodying a dual responsibility:

  • Act as a steward and advocate for a data-driven culture.
  • Lead projects and provide support to clients throughout various initiatives.

Leadership Responsibilities:

  • Engage in estimating and establishing quality benchmarks for projects;
  • Serve as a technical authority for project teams;
  • Stay informed on emerging trends, best practices, and innovative tools related to data (Analytics, Machine Learning, Artificial Intelligence, etc.).
  • Contribute to shaping the vision for data practices (Analytics & AI) within the organization and assist in enhancing the service offerings and tools utilized;
  • Promote the democratization of data across Nurun;

Data Consulting Responsibilities:

  • Assist in performance evaluation, defining measurement goals, and monitoring performance during the initial stages of projects;
  • Advise on and implement best practices for data organization and structuring.
  • Develop dashboards and configure visualization tools for clients.
  • Facilitate the implementation of performance monitoring tools and leverage them to assess the effectiveness of clients' digital solutions.
  • Support clients in integrating machine learning models into their offerings.

Qualifications:

  • Bilingual: fluent in both French and English (essential).
  • Over 5 years of professional experience.
  • Bachelor's degree in mathematics, statistics, computer science, business administration, economics, or finance.
  • Comfortable presenting and sharing enthusiasm for data with team members.
  • Proficient in accessing various databases and crafting advanced queries for data analysis. Strong knowledge of SQL, with expert proficiency in Python or R.
  • Demonstrated statistical expertise in machine learning, including model creation and maintenance, as well as mentoring analysts in effective problem-solving methodologies.
  • Advanced understanding of data models, infrastructure, and architecture.
  • Ability to navigate ambiguity, particularly with clients who may not fully grasp the implications of their data-related decisions.
  • Proven knowledge in data quality, including various cleansing techniques and data integrity verification.
  • Strong skills in data visualization using tools such as Tableau, Looker, PowerBI, Quicksight, or similar.
  • Ability to synthesize and analyze diverse data sets to provide clear and accurate insights to varied audiences.
  • Familiarity with Google Analytics 4.

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