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Compensation Data Analytics Jobs in Toronto, ON (NOW HIRING)

Specialist, Data & Analytics (HR)

Toronto, ON · On-site

CA$74K - CA$93K/yr

Job Summary As the Specialist, Data & Analytics, you will play a pivotal role in analyzing and ... We believe compensation should be transparent, equitable, and reflective of your experience and ...

Transform compensation data into strategic insights -conducting rigorous market analysis, competitive benchmarking, and equity assessments to inform recommendations that position RBC as a competitive ...

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Compensation Data Analytics information

What is compensation data analytics?

Compensation data analytics is the process of collecting, analyzing, and interpreting data related to employee compensation, such as salaries, bonuses, and benefits. This field helps organizations make informed decisions about pay structures, ensure competitive and equitable compensation, and comply with legal requirements. By leveraging data analytics, companies can identify trends, address pay disparities, and optimize their compensation strategies to attract and retain top talent.

What are the key skills and qualifications needed to thrive as a Compensation Data Analytics professional, and why are they important?

To thrive as a Compensation Data Analytics professional, you need strong analytical skills, a solid understanding of compensation structures, and a degree in fields like HR, finance, or statistics. Familiarity with HR information systems (HRIS), data visualization tools like Tableau or Power BI, and proficiency in Excel or statistical software such as R or Python are commonly required. Attention to detail, problem-solving abilities, and effective communication skills help you translate complex data into actionable insights for stakeholders. These skills ensure accurate, data-driven compensation strategies that support organizational goals and fair employee practices.

What is the difference between Compensation Data Analytics vs Compensation Analyst?

AspectCompensation Data AnalyticsCompensation Analyst
CredentialsDegree in HR, Business, or Data Analytics; often certifications in data analysisDegree in HR, Business, or related field; HR certifications common
Work EnvironmentData-focused, analytical tasks, often in HR or compensation departmentsHR teams, compensation planning, employee benefits
Industry UsageUsed across industries for data-driven compensation strategiesPrimarily in HR and compensation departments within various industries
Search & Comparison IntentFocus on data analysis skills and tools for compensation dataFocus on salary structures, benefits, and employee compensation policies

Compensation Data Analytics involves analyzing large datasets to inform compensation strategies, requiring strong data skills. Compensation Analysts focus on designing and managing salary structures and benefits. Both roles collaborate but differ mainly in their focus—data analysis versus policy implementation.

What is the highest paying job in data analytics?

The highest paying roles in data analytics typically include Data Science Directors, Chief Data Officers, and Analytics Executives, with salaries often exceeding $150,000 annually. These positions require advanced skills in statistical analysis, machine learning, and leadership, and are usually found in large corporations or tech companies.

What jobs make $1,000,000 a year?

In compensation data analytics, roles such as chief data officer, senior data scientist, or executive-level positions in finance and technology can reach or exceed $1 million annually, often through base salary, bonuses, and stock options. These high earnings typically require extensive experience, advanced skills in data modeling and analytics tools, and leadership responsibilities. Such compensation is more common in large corporations or successful startups with significant revenue and growth potential.

Will AI replace a data analyst?

AI tools can automate routine data processing and analysis tasks, but the role of a data analyst involves interpreting complex data, providing insights, and communicating findings, which require human judgment and domain expertise. Therefore, while AI may augment a data analyst's work, it is unlikely to fully replace the role in the near future.

How does a Compensation Data Analytics professional typically collaborate with HR and business leaders to inform pay decisions?

Compensation Data Analytics professionals work closely with HR teams and business leaders by providing data-driven insights that guide salary structures, incentive plans, and pay equity initiatives. They interpret data from salary surveys, internal pay records, and market trends, translating complex analyses into actionable recommendations. Regular meetings and presentations are common, ensuring that stakeholders understand compensation trends and can make informed decisions that support organizational goals. Effective communication and collaboration are key, as these professionals often bridge the gap between technical analytics and strategic HR planning.

What jobs pay 500,000 a year in the US?

In compensation data analytics, senior roles such as Chief Compensation Officer or Compensation Director can reach or exceed $500,000 annually, especially in large corporations or industries with high compensation packages. These positions often require extensive experience, advanced certifications, and expertise in data analysis, market trends, and compensation strategy.
What job categories do people searching Compensation Data Analytics jobs in Toronto, ON look for? The top searched job categories for Compensation Data Analytics jobs in Toronto, ON are:
Infographic showing various Compensation Data Analytics job openings in Toronto, ON as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

CA$28/hr

Other

Posted 19 days ago


Job description

About us

CDI College is Canada's largest private college network with over 50 years of educational excellence with 23 campuses in British Columbia, Alberta, Ontario, Quebec and Manitoba. Our innovation and dynamism shine through a range of forward-thinking programs. We are a leading Canadian career training institution, dedicated to quality education and student success. Established in 1970, we offer over 50 diploma and certifications programs across various disciplines such as business, healthcare, technology, and art and design.

Job Status: Part-time, Remote (Weekend Availability Required)
Start Date: ASAP
Working Hours: Ongoing, Part-time
Compensation: $28/hour
Campus: CDI College - Brampton

Position Summary
The Data Analytics Instructor is responsible for delivering high-quality instruction and supporting student success in alignment with the program curriculum. This role focuses on engaging teaching, practical application of data analytics concepts, and fostering an inclusive learning environment.

Key Responsibilities

  • Deliver lectures, workshops, and hands-on training for the Data Analytics program.
  • Develop and implement lesson plans aligned with curriculum objectives.
  • Provide timely feedback on assignments and projects to support student progress.
  • Maintain accurate records of attendance and academic performance.
  • Contribute to curriculum enhancement and continuous improvement initiatives.
  • Collaborate with faculty to ensure consistent and high-quality program delivery.
  • Support student achievement, employability, and overall well-being.

Qualifications

Education & Experience

  • Degree in Data Analytics, Data Science, Computer Science, Mathematics, Statistics, or a related field.
  • Minimum 2 years of industry experience in data analytics or a related field.
  • Minimum 2 years of teaching experience at the post-secondary level (preferred).

Skills & Competencies

  • Strong ability to teach and apply data analytics concepts through real-world projects.
  • Excellent communication and presentation skills.
  • Effective problem-solving and organizational abilities.
  • Collaborative approach with a focus on student engagement and success.
  • Familiarity with Learning Management Systems (LMS).

Technical Knowledge

  • Proficiency in Python and data analysis libraries.
  • Working knowledge of big data tools and technologies (e.g., Spark, Hadoop, Tableau, R, NoSQL).
  • Understanding of data analytics fundamentals and methodologies (e.g., Agile, Lean).
  • Basic knowledge of artificial intelligence concepts.

Don't hold back!-apply today, even if you do not tick every skills list. We cherish diverse skill sets, knowing your unique experiences and perspectives enrich our dynamic team.
We are proudly Canadian - rooted in our diverse communities, guided by our values, and committed to growing together from coast to coast.