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Added 15 mins ago
Human Resources Information System Analyst
Infotree Global Solutions
Montreal, QC
Contract
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Added 31 mins ago
Business Systems Analyst
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Associate Director, AI Products Development Lead
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Senior Governance & Control Analyst-1
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Added 1 hour ago
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Added 1 hour ago
Salesforce Business Analyst – Financial Services Cloud (FSC)
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Added 1 hour ago
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Added 1 hour ago
Data Analyst, Principal
Dayforce
Canada
As a Principal Data Analyst, you are a highly analytical, technically strong, forward-thinking problem solver who thrives on turning data into strategic insight and building modern decision…
Added 1 hour ago
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Financial Business Analyst - ITS - FT Admin Contract
Humber College
Toronto, ON
Contract
Position Title: Business Analyst – Financial Business Analyst

Dayforce

Data Analyst, Principal

Canada

Apply by: Nov 27, 2026
Posting language: English
Posted: Oct 1, 2026

Apply About employer

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Original job description

Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region.

Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce.

Our brand promise - Makes Work Life Better™ - Reflects our commitment to employees, customers, partners and communities globally.

About the opportunity

As a Principal Data Analyst, you are a highly analytical, technically strong, forward-thinking problem solver who thrives on turning data into strategic insight and building modern decision products. You will play a pivotal role within the Decision Intelligence team, combining deep analytical expertise with hands-on technical skills to solve complex business problems using enterprise data, business intelligence, artificial intelligence (AI), and automation.

This is a hands-on technical role with significant visibility across the organization. You will work directly with senior leaders and cross-functional stakeholders while personally designing and building analytical solutions - ranging from enterprise semantic models and Power BI experiences to AI-powered applications and agents. Your work will directly influence strategic decisions and help evolve how the enterprise consumes data, insights, and AI.

What you'll get to do

Promote Data-Driven Decision-Making: Translate ambiguous business questions into analytical solutions that go beyond stated needs - proactively surfacing insights, root causes, opportunities, and recommended actions that guide executive strategy and operational excellence.
Build Modern Decision Products: Personally design and build analytical products ranging from scalable semantic models and advanced Power BI experiences to AI-powered analytical applications and agents. Select the appropriate interface and technology based on the business problem rather than defaulting to traditional dashboards.
Build AI-Powered Analytical Solutions: Design, prototype, build, and help productionize AI-enabled analytical applications and agents that combine enterprise data, semantic context, large language models (LLMs), APIs, and tools to answer business questions, generate insights, and automate analytical workflows.
Collaborate Across the Business: Partner with leaders in designated departments and other domains to define key metrics, interpret performance results, understand business context, and connect analytics and AI solutions to financial, operational, customer, and growth objectives.
Engineer Trusted Analytical Foundations: Build and maintain reliable data models, metric definitions, semantic models, and analytical logic. Troubleshoot data gaps and partner with data engineering and governance teams to strengthen data quality, lineage, consistency, and trust.
Apply Practical AI and Automation: Identify high-value opportunities for AI and automation, then move beyond ideation to working solutions. Apply techniques such as tool/function calling, structured outputs, retrieval and grounding, context engineering, and agentic workflows where they provide measurable business value.
Evaluate for Accuracy and Reliability: Develop practical approaches to test and monitor AI-enabled analytical solutions, including grounding, hallucination and accuracy testing, regression testing, observability, and human review. Understand when deterministic analytics, traditional machine learning, or an LLM-based approach is most appropriate.
Communicate with Confidence: Synthesize complex analyses and technical solutions into clear, compelling narratives and present actionable insights, tradeoffs, and recommendations to senior leadership.

Skills and experience we value

Bachelor's degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Business Analytics, or a related analytical field; Master's degree preferred.
10+ years of progressive experience in data analytics, business intelligence, analytical engineering, data science, decision science, or related technical roles, preferably in an enterprise SaaS, technology, consulting, or complex business environment.
Strong SQL, data modeling, and analytical engineering skills, with hands-on experience building enterprise analytics solutions using platforms such as Power BI. Candidates should be comfortable working directly in Power BI when needed, including semantic models, DAX, performance optimization, advanced dashboards, and executive-facing analytical products.
Strong hands-on Python skills and comfort working with APIs, Git, JSON, testing and debugging, notebooks, and modern development workflows used to build analytical and AI-enabled solutions.
Demonstrated hands-on experience building AI/LLM applications beyond the use of AI productivity tools or commercial chat applications. Experience should include several of the following: agentic workflows, tool/function calling, structured outputs, retrieval/RAG, context engineering, prompt design, API integration, and evaluation frameworks.
Demonstrated track record of personally designing and building AI-enabled analytical products or agentic systems from prototype toward production. Candidates should be prepared to discuss architecture, implementation decisions, evaluation methods, failures, tradeoffs, and lessons learned from systems they personally built.
Strong understanding of semantic modeling, metric design, KPI frameworks, business definitions, data quality, lineage, and governance practices needed to provide trusted context to both enterprise reporting and AI-enabled analytical experiences.
Demonstrated ability to translate ambiguous business questions into structured analytical and technical approaches, identify root causes, quantify business impact, and determine when a problem is best solved with SQL or deterministic software, traditional analytics or machine learning, a BI experience, or an LLM/agentic solution.
Experience evaluating AI systems for accuracy, grounding, reliability, and business usefulness, including approaches such as test datasets, hallucination testing, regression testing, observability, human review, and appropriate controls for enterprise use.
Proven experience leading complex analytical or AI initiatives from concept through implementation with minimal oversight, including requirements definition, stakeholder alignment, hands-on development, testing, delivery, adoption, and ongoing optimization.
Experience partnering with senior leaders and cross-functional stakeholders to define success metrics, interpret performance trends, and connect analytical and AI solutions to financial, operational, customer, and growth outcomes.
Exceptional communication, analytical reasoning, and business acumen, with the ability to synthesize complex data and technical concepts into clear narratives, evaluate tradeoffs, prioritize work based on business value, and influence decisions at senior levels.
High degree of intellectual curiosity, ownership, technical judgment, and attention to detail. We value demonstrated building experience over theoretical familiarity; candidates should be prepared to discuss systems they personally designed and implemented. Experience working in the Human Capital Management industry is preferred.

What’s in it for you

Dayforce is fueled by the diversity of our talented employees. We are an equal opportunity employer and consider and embrace ALL individuals and what makes them unique. We believe our employees should be happy and healthy, with peace of mind and a sense of fulfillment.

We encourage individuals to apply based on their passions.

Dayforce encourages personal and professional growth. We offer excellent time away from work programs, comprehensive wellness initiatives and recognition through competitive pay and benefits.

With a commitment to community impact, including volunteer days and our charity, Dayforce Cares we provide opportunities for you to thrive both in your career and personal life. Our focus is not just on your job but on supporting you to be the best version of yourself.

This job posting is for an existing vacancy

Artificial intelligence may be used in the screening, assessment, or selection of applicants for this position.

About the Salary Ranges

Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate’s experience, skills, budget and location. Our company is committed to providing a fair, equitable, and competitive package that reflects the value an individual brings to the organization.

Proficiency in English is required for this position as this role will regularly interact with English-speaking stakeholders, co-workers, managers and/or clients across the world. Further, our back office support teams, including but not limited to Human Resources, are primarily English speaking. Employees need to be able to communicate with these departments in English to appropriately administer their business relationship. Due to the significant high volume of interactions with these English-speaking co-workers, managers, stakeholders and/or clients, which is inherent to this position, it is not possible to reorganize the company's activities to avoid this requirement.

Fraudulent Recruiting

Beware of fraudulent recruiting. Legitimate Dayforce contacts will use an @dayforce.com email address. We do not request money, checks, equipment orders, or sensitive personal data during the recruitment process. If you have been asked for any of the above, or believe you have been contacted by someone posing as a Dayforce employee, please refer to our fraudulent recruiting statement found here: https://www.dayforce.com/be-aware-of-recruiting-fraud

Dayforce actively monitors all job applications to ensure authenticity. Submissions determined to be fraudulent or misleading will be declined from the recruitment process

Pour consulter cette offre d'emploi en français, veuillez utiliser le lien: https://jobs.dayforcehcm.com/fr-CA/mydayforce/alljobs

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More about this job

Responsibilities

You will design and build modern decision products, including AI-powered applications and semantic models, to drive strategic business insights. You will also collaborate with cross-functional stakeholders to define key metrics and ensure data quality and governance across the enterprise.

Requirements

Candidates must have 10+ years of experience in data analytics or related technical roles with strong proficiency in SQL, Python, and Power BI. A bachelor's degree in an analytical field is required, with a preference for a master's degree and experience in AI/LLM application development.

Skills

Data analysis
SQL
Power BI
Python
Data modeling
Artificial intelligence
Machine learning
LLM
Semantic modeling
DAX
API integration
Prompt design
Retrieval-augmented generation
Business intelligence
Analytical engineering
Strategic insight

Benefits

Time away from work programs
Comprehensive wellness initiatives
Competitive pay
Charity programs

Visa sponsorship

Not detected in the job text

Keywords

Data Analyst
Decision Intelligence
SaaS
Human Capital Management
Power BI
SQL
Python
LLM
Artificial Intelligence
Semantic Modeling
DAX
API
Git
JSON
RAG
Agentic workflows
Business Intelligence
Data Engineering
Data Governance
KPI
Metric design
Predictive analytics
Machine learning
Enterprise data
Automation
Strategic planning
Stakeholder management
Data quality
Cloud HCM
Analytical engineering

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