Lead Analyst, People Analytics
New
CanadaFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLBusiness IntelligenceData visualizationR
Requirements
- 5+ years of experience in analytics, business intelligence, or a quantitative research role, preferably within People/HR analytics.
- Strong understanding of applied research methods, including experimental design, statistical inference, and model validation.
- Proven ability to translate complex data analysis into actionable insights for senior, non-technical stakeholders.
- Experience partnering with leadership teams in a consultative, advisory capacity.
- Strong technical proficiency in SQL, and either Python or R, along with BI and analytics tools.
- Advanced data visualization and storytelling skills with a focus on decision impact.
- Experience working with AI tools to enhance analytical workflows is a plus.
- Bachelor’s degree in Psychology, Statistics, Business Analytics, or a related field (or equivalent experience).
- Strong ability to manage sensitive data with discretion and maintain high standards of integrity.
Responsibilities
- Partner with HR and business leaders to understand decision-making needs and design people analytics solutions that connect workforce data to strategic outcomes.
- Build and maintain a suite of interconnected dashboards and reporting tools, ensuring they are intuitive, adoption-focused, and decision-oriented.
- Apply rigorous analytical and research methods to workforce data, ensuring statistical validity and identifying bias, limitations, and meaningful insights.
- Translate complex analyses into clear executive-level insights, framing outputs around decisions, implications, and business impact.
- Develop foundational people analytics frameworks and knowledge models that explain key drivers such as talent density, hiring efficiency, and workforce performance trends.
- Act as a strategic advisor to HR leadership on organizational and workforce challenges using data-driven recommendations.
- Leverage AI-enabled workflows and analytics tools to streamline analysis, documentation, and insight generation.
- Work hands-on with tools such as SQL, Python or R, and enterprise BI platforms to build, validate, and deliver analytical solutions.
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