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Data Science Associate Jobs in Ontario (NOW HIRING)

Upshop

Data Engineering Manager

Mississauga, ON · On-site

Its unified platform simplifies and enhances associate tasks, promoting smarter and more ... Partner with BI, Data Science, and Product teams to bridge business requirements into scalable ...

KPMG

Manager, ML/AI Engineer, Data & AI

Toronto, ON · On-site

University degree in computer science, engineering, data science, mathematics, or a related ... Cloud AI / ML certifications (e.g., Azure AI Engineer Associate or better, AWS Machine Learning ...

U Education Management Pvt. Ltd.

We\- re one of the few applications of AI\/ data science that actually has a massive market and ... Associate\n \n \n \n \n Job function \n \n \n Information Technology\n \n \n \n \n \n \n

Next Generation

Associate Scientist

Dublin, ON

$45K - $48K/yr

Associate Scientist This position is a support role within the Analytical Method Sciences pillar ... Empower Chromatography Data system master data. The Role: Provide end user support by ...

Swiss Re

Associate Pricing Actuary

Toronto, ON · Hybrid

CA$74K - CA$92K/yr

About the Role As an Associate Pricing Actuary, you'll be at the intersection of data analysis ... Apply actuarial and data science techniques to improve profitability analysis. * Coordinate rate ...

Walmart

(CAN) Solution Consultant II

Mississauga, ON · On-site

Data engineering or data science exposure is a plus. Leadership Expectations: Respect the Individual: Demonstrates and encourages respect for others; drives a positive associate and customer ...

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All JobsData Science Associate JobsData Science Associate Jobs in Ontario

Data Science Associate information

See Ontario salary details

$10

$45

$98

How much do data science associate jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for data science associate in Ontario is $45.59, according to ZipRecruiter salary data. Most workers in this role earn between $23.08 and $61.78 per hour, depending on experience, location, and employer.

How does a Data Science Associate typically collaborate with other departments or teams within an organization?

Data Science Associates frequently work cross-functionally, partnering with teams such as engineering, product management, and business analytics to understand project requirements, share findings, and implement data-driven solutions. Collaboration often involves translating complex data results into actionable insights for non-technical stakeholders, ensuring alignment on project goals and deliverables. This role requires strong communication skills, as associates routinely participate in meetings, present analyses, and gather feedback to refine their models or analyses. Effective teamwork helps ensure that data science initiatives support broader business objectives.

Is data science dead in 10 years?

Data Science Associate roles are expected to remain relevant in the next decade as organizations continue to rely on data-driven decision making. Advances in automation and AI may change some tasks, but skills in statistical analysis, programming, and machine learning will still be valuable for interpreting complex data. Continuous learning and adapting to new tools like Python, R, and cloud platforms will be important for future success in the field.

What are Data Science Associates?

Data Science Associates are early-career professionals who support data-driven projects by collecting, cleaning, analyzing, and interpreting large datasets. They typically work under the guidance of more experienced data scientists and help build predictive models, generate reports, and provide insights to inform business decisions. This role often requires proficiency in programming languages like Python or R, familiarity with statistical methods, and strong problem-solving skills. Data Science Associates play a crucial part in transforming raw data into actionable information for organizations.

What are the key skills and qualifications needed to thrive as a Data Science Associate, and why are they important?

To thrive as a Data Science Associate, you need strong analytical skills, a solid foundation in statistics and mathematics, and proficiency in programming languages like Python or R, often supported by a degree in data science, computer science, or a related field. Familiarity with machine learning frameworks, data visualization tools, and database systems such as SQL is typically required. Excellent problem-solving abilities, effective communication, and collaboration skills help you translate complex data insights into actionable business strategies. These skills are vital for extracting meaningful value from data and supporting data-driven decision-making within organizations.

What is the difference between Data Science Associate vs Data Analyst?

AspectData Science AssociateData Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles prefer certifications in data analysis or programmingBachelor's degree in Statistics, Mathematics, or related field; often no advanced certifications required
Work EnvironmentCollaborates with data scientists and engineers; involved in building models and algorithmsFocuses on data collection, cleaning, and reporting; supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms for data-driven projectsCommon across various industries for business insights and reporting

The Data Science Associate role typically involves more technical work like building models and applying machine learning, whereas Data Analysts focus on interpreting data and creating reports. Both roles require strong analytical skills, but Data Science Associates often have a deeper understanding of programming and statistical modeling.

What are the most commonly searched types of Data Science jobs in Ontario? The most popular types of Data Science jobs in Ontario are:
What are popular job titles related to Data Science Associate jobs in Ontario? For Data Science Associate jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Data Science Associate jobs in Ontario look for? The top searched job categories for Data Science Associate jobs in Ontario are:
What cities in Ontario are hiring for Data Science Associate jobs? Cities in Ontario with the most Data Science Associate job openings:
Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Ontario as of June 2026, with employment types broken down into 84% Full Time, 13% Part Time, 2% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $94,837 per year, or $45.6 per hour.

Senior Consultant, Microsoft Fabric Data Engineer, Data & AI

KPMG

Toronto, ON

Full-time

Posted 2 days ago

Job description

Overview

At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.

Are you a talented leader with a proven track record for motivating teams and delivering exceptional client service?

Our team is looking for a Data Engineer with deep hands-on expertise in Microsoft Fabric and strong consulting capabilities. This role will support and lead data platform modernization initiatives, helping clients migrate from legacy and onpremise environments to scalable, secure, and unified analytics platforms leveraging Microsoft Fabric, OneLake, and Azure-native services.


What you will do
  • Partner with clients to understand business goals, gather requirements, and translate them into actionable technical designs and delivery plans using Microsoft Fabric.
  • Work with engagement teams to translate business and analytics requirements into endtoend data strategies, including ingestion, transformation, semantic modeling, and analytics enablement.
  • Contribute to solution architecture design for repeatable, scalable, and costoptimized analytics platforms using Microsoft Fabric components.
  • Lead delivery of modern data platforms leveraging Fabric Lakehouse, Data Warehouse, Data Engineering, and Real-Time Analytics workloads.
  • Design and implement data ingestion and transformation pipelines using Fabric Data Factory, notebooks, and Spark.
  • Implement medallion architecture patterns (Bronze, Silver, Gold) using Fabric Lakehouse and OneLake.
  • Develop scalable batch and streaming pipelines using Spark, Eventstreams, and real-time ingestion patterns.
  • Build and optimize semantic models for downstream analytics and reporting in Power BI.
  • Apply CI/CD and engineering best practices including version control, automated deployment, testing, and release management for Fabric workloads.
  • Establish and operationalize governance across Fabric using Microsoft Purview, role-based access control, and data lineage.
  • Support testing, performance tuning, and production releases across Fabric workloads.
  • Proactively contribute to creation of presentation materials and client-facing documentation related to data and analytics initiatives.
  • Provide technical leadership and mentorship to junior team members.

What you bring to the role
  • University degree in computer engineering, computer science, mathematics, data science, or related disciplines.
  • 4+ years of professional experience in Data Engineering, Analytics Engineering, Business Intelligence, or a related field.
  • 2+ years of hands-on experience with Microsoft Fabric or Azure Synapse / Azure Data Engineering services.
  • Strong proficiency in SQL and solid understanding of modern data modeling principles and data warehousing concepts.
  • Proficiency in Python (or similar languages) for data processing, automation, and analytics workflows.
  • Hands-on experience with Spark-based data processing and notebook-driven development.
  • Experience with Fabric Lakehouse, Data Warehouse (SQL Endpoint), OneLake, and semantic modeling.
  • Experience supporting data platform modernization and Azure-based migration initiatives.
  • Experience applying CI/CD practices to data and analytics solutions.
  • Strong understanding of data governance, security, and access control within Microsoft ecosystems.
  • Experience collaborating with cross-functional teams to solve complex data challenges.
  • Familiarity with Power BI and downstream analytics enablement.

Certifications (Preferred)

  • Microsoft Certified: Fabric Analytics Engineer Associate
  • Microsoft Certified: Azure Data Engineer Associate
  • Power BI Data Analyst certification
  • Other relevant Microsoft Azure or data engineering certifications

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program. 

Providing you with the support you need to be at your best


Our Values, The KPMG Way

Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.

Adjustments and accommodations throughout the recruitment process

At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.

AI Usage

Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.

We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.

Qualifications:
  • University degree in computer engineering, computer science, mathematics, data science, or related disciplines.
  • 4+ years of professional experience in Data Engineering, Analytics Engineering, Business Intelligence, or a related field.
  • 2+ years of hands-on experience with Microsoft Fabric or Azure Synapse / Azure Data Engineering services.
  • Strong proficiency in SQL and solid understanding of modern data modeling principles and data warehousing concepts.
  • Proficiency in Python (or similar languages) for data processing, automation, and analytics workflows.
  • Hands-on experience with Spark-based data processing and notebook-driven development.
  • Experience with Fabric Lakehouse, Data Warehouse (SQL Endpoint), OneLake, and semantic modeling.
  • Experience supporting data platform modernization and Azure-based migration initiatives.
  • Experience applying CI/CD practices to data and analytics solutions.
  • Strong understanding of data governance, security, and access control within Microsoft ecosystems.
  • Experience collaborating with cross-functional teams to solve complex data challenges.
  • Familiarity with Power BI and downstream analytics enablement.

Certifications (Preferred)

  • Microsoft Certified: Fabric Analytics Engineer Associate
  • Microsoft Certified: Azure Data Engineer Associate
  • Power BI Data Analyst certification
  • Other relevant Microsoft Azure or data engineering certifications

KPMG Ontario Region Pay Range Information

The expected base salary range for this position is $77,000 to $102,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program.

KPMG BC Region Pay Range Information   

The expected base salary range for this position is $73,000 to $100,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills & competencies, and unique qualifications. In addition, KPMG offers a comprehensive and competitive Total Rewards program. 

Providing you with the support you need to be at your best

Education:UNAVAILABLEEmployment Type: FULL_TIME

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