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Data Scientist; Master's; Montreal Scientifique des données; diplôme de maîtrise Date de début

Job in Montréal, Province de Québec, G4F, Canada
Listing for: UNAVAILABLE
Full Time position
Listed on 2026-10-26
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst, AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 120000 CAD Yearly CAD 90000.00 120000.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist (Master's) - Montreal (2027 Start Date) | Scientifique des données (diplôme de maîtrise Date de début
Overview

About Groupe d’analyse (Analysis Group)

Make an impact at Groupe d'analyse (Analysis Group), where we provide our clients with thoughtful, pragmatic solutions to their most challenging business and litigation problems. Groupe d'analyse (Analysis Group) is one of the largest economics consulting firms, with more than 1,500 professionals across 15 offices in North America, Europe, and Asia. Since 1981, we have provided expertise in economics, finance, health care analytics, and strategy to top law firms, Fortune Global 500 companies, and government agencies worldwide.

Our internal experts, together with our network of affiliated experts from academia, industry, and government, offer our clients exceptional breadth and depth of expertise.

About the Data Scientist position:

Data Scientists at Groupe d'analyse (Analysis Group) help design, implement and maintain creative solutions to high-profile business challenges in finance, economics and health care across multiple industries. To this end, Data Scientists are responsible for staying abreast of new developments in technology and data science, including generative artificial intelligence (“AI”), and communicating within the firm to help identify opportunities for cutting‑edge tools, applications and data sources.

Career development at Groupe d'analyse (Analysis Group) includes opportunities for growth in technical skills as well as in project management, analytical strategy and collaborative business development, depending on individual skills and interests, and with support and mentorship from senior staff.

Key Responsibilities:

  • Working with project teams to address data science and computing challenges.
  • Identifying opportunities for leveraging cutting‑edge technology to enhance service offerings.
  • Acting as a resource and participating in client engagements and research as part of the project team.
  • Maintaining up‑to‑date knowledge of computing tools, providing technical training and helping to grow the in‑house knowledge base of the data science landscape.
  • Acting as a generalist in data science projects, influencing the choice of technology and methodology.

Activities:

  • Conducting advanced statistical and mathematical analyses to address complex research questions and derive actionable insights that support client decision‑making.
  • Developing end‑to‑end data engineering and machine learning production systems for full stack data science projects.
  • Using Natural Language Processing and generative AI to work with unstructured data (EMR, social media and other).
  • Optimizing procedures for managing and accessing large databases (e.g., insurance claims, electronic health records, financial transactions).
  • Creating interactive analytics portals and data visualizations (e.g., using R/ R-Shiny, Python/Flask, D3).
  • Leveraging on grid and cloud computing environments, and developing software packages in R, Python, and other object‑oriented languages.
  • Establishing optimized procedures for repetitive or computationally intensive tasks.

Qualifications:

  • Master’s degree with three years of relevant work experience required ideally in Computer Science, Mathematics, Statistics, Economics or other relevant scientific degree.
  • Ability to apply advanced statistical and mathematical methods to address complex research questions, with a strong foundation in independent problem‑solving and analytical thinking.
  • Strong credentials and experience in working with both structured and unstructured data, along with data visualization skills, are required.
  • Proficiency in Python and/or R is required, with project experience in either language.
  • Familiarity with generative AI concepts (e.g., embeddings, vector search, retrieval‑augmented generation, prompt design, tool calling,…
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