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Business Data Analyst AI​/ML

Job in Sherbrooke, Province de Québec, Canada
Listing for: BRP
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Business Systems/ Tech Analyst, Data Scientist
Job Description & How to Apply Below
JOB DESCRIPTION

Be a part of a fast-paced culture and community in a startup-like environment inside one of the most successful organizations in Québec. We are focused on building a highly talented and ambitious team from the ground up that revolutionizes the way we work around Data & Analytics  are a team that has the potential to unlock tremendous value for the organization and you have the unique opportunity to be part of it from the beginning.

Join BRP's central Data & Analytics team (DNA) as a Business Data Analyst AI/ML and bring your analytical skills and business insight to our dynamic team. This role is perfect for someone who seeks to blend their understanding of business intelligence with the predictive power of data science to unlock new opportunities for BRP.

YOU'LL HAVE THE OPPORTUNITY TO:

Use Case Framing & Business Value

  • Partner with business stakeholders to understand objectives, constraints, and pain points

  • Turn ambiguous problems into structured analytics / AI opportunities (problem statement, hypotheses, success criteria)

  • Build lightweight business cases (value drivers, assumptions, expected benefits, measurement approach)

  • Support prioritization by comparing opportunities across value, feasibility, and delivery complexity

  • Hands-on Analysis & Feasibility

  • Identify and validate the right data sources; assess data completeness, granularity, and fitness-for-purpose

  • Perform exploratory analysis and data profiling to surface trends, anomalies, and data quality issues

  • Run descriptive/diagnostic analyses and basic statistical assessments to validate hypotheses and quantify impact

  • Create simple analytical prototypes to validate stakeholder needs, clarify assumptions, and support knowledge transfer to Data Scientists before full model development

  • Requirements & Delivery Enablement

  • Translate stakeholder needs into clear analytical and functional artifacts for Data Scientists and Machine Learning Engineers (problem statements, hypotheses, data requirements, acceptance criteria)

  • Define metrics and measurement plans (baselines, KPIs, guardrails) so impact can be tracked objectively

  • Contribute to documentation (assumptions, definitions, data logic) to improve reusability and alignment

  • Insight Communication & Data Storytelling

  • Produce clear, decision-ready narratives and visuals for technical and non-technical audiences using data visualization and communication tools adapted to the context

  • Present findings, options, and trade-offs with a strong recommendation mindset

  • Facilitate workshops to align stakeholders on definitions, processes, and what “success” means

  • Continuous Improvement & Data Quality Mindset

  • Flag recurring data issues and propose pragmatic fixes (logic, definitions, upstream processes, monitoring needs)

  • Help improve team templates and ways of working (intake, discovery, feasibility checklist, measurement framework)

  • Stay curious about analytics and AI/ML trends and how they translate into practical business value

  • YOU'LL THRIVE IN THIS ROLE IF YOU HAVE THE FOLLOWING SKILLS AND QUALITIES:

  • MSc (preferred) or BSc in Statistics, Data Science, Computer Science, Business Intelligence, Analytics, Engineering, Economics, or related field

  • ~3–5 years of experience in a Business Data Analyst, Analytics Consultant, Data Analyst, BI Analyst or similar role

  • Strong hands-on experience with data analysis and exploration (Python preferred; pandas, numpy, basic statistics)

  • Solid SQL skills and experience working with data warehouses (Snowflake is a plus)

  • Proficiency with data visualization and communication tools (e.g., Power BI, PowerPoint, Lucidchart) and ability to craft clear, impactful messages tailored to the audience

  • Ability to assess data quality, perform exploratory analyses, and interpret results critically

  • Strong business acumen and ability to link data insights to business value

  • Comfortable working with AI/ML teams, with a good understanding of analytics and machine learning concepts (no need to build models)

  • Excellent communication skills and ability to explain analytical insights to non-technical stakeholders

  • Comfortable in French (spoken/written); team communication is primarily in English, strong English…

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