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Data Science Fall Internship Jobs in Ontario (NOW HIRING)

... Fall co-op term (September - December 2026). This role is ideal for a student with a strong ... Currently enrolled in a post-secondary program in Computer Science, Data Science, Engineering ...

Bachelor's degree in business, Finance, Accounting, Computer Science, Information Systems ... Experience through work, internships, co-op placements, or academic projects with: * Data analysis ...

... sciences and food and beverage industries. Our mission, vision, and core values put client ... Join our firm for an internship journey where you'll dive into real-world project work, learn from ...

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Data Science Fall Internship information

See Ontario salary details

$13K

$77.4K

$189K

How much do data science fall internship jobs pay per year?

As of Aug 8, 2026, the average yearly pay for data science fall internship in Ontario is $77,358.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,000.00 and $117,500.00 per year, depending on experience, location, and employer.

What types of projects can I expect to work on during a data science fall internship?

As a Data Science Fall Intern, you can expect to work on projects involving data cleaning, exploratory data analysis, and the development of predictive models using real-world datasets. Interns often collaborate with full-time data scientists and cross-functional teams to solve business problems, such as improving user engagement, optimizing processes, or generating actionable insights from large data sets. You may also participate in regular team meetings, present findings, and contribute to ongoing research or tool development. This hands-on experience helps you build both technical and communication skills within a dynamic and supportive environment.

What are the key skills and qualifications needed to thrive as a data science fall intern, and why are they important?

To thrive as a Data Science Fall Intern, you generally need a solid foundation in statistics, programming (often Python or R), and data analysis, typically supported by coursework or experience in computer science, mathematics, or related fields. Familiarity with tools like pandas, scikit-learn, SQL, and data visualization libraries, as well as version control systems like Git, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help interns interpret data insights and collaborate with team members. These competencies are essential for producing actionable analyses and contributing meaningfully to data-driven projects in a short-term, fast-paced internship environment.

What is a data science fall internship?

A Data Science Fall Internship is a temporary, structured work experience offered by organizations during the fall semester, designed for students or recent graduates interested in data science. Interns typically work on real-world projects involving data collection, analysis, machine learning, and visualization under the guidance of experienced data scientists. This internship provides hands-on experience, exposure to industry tools and techniques, and helps participants build valuable skills for future careers in data science. It also offers networking opportunities and a chance to explore potential career paths within the field.

What is the difference between Data Science Fall Internship vs Data Analyst Intern?

AspectData Science Fall InternshipData Analyst Intern
Required CredentialsEnrolled in or recent graduate of a related field (e.g., Data Science, Computer Science, Statistics)Enrolled in or recent graduate of a related field (e.g., Data Analysis, Business, Statistics)
Work EnvironmentTech companies, startups, research labs, often collaborative and project-basedBusiness firms, consulting agencies, often focused on reporting and data visualization
Employer & Industry UsageUsed by tech firms, finance, healthcare, and academia for entry-level talentCommon in corporate, marketing, and consulting sectors for supporting decision-making

The Data Science Fall Internship and Data Analyst Intern roles share similarities in required education and work environment but differ in focus. Data Science internships emphasize machine learning, programming, and statistical modeling, while Data Analyst internships focus more on data visualization, reporting, and business insights. Both are valuable entry points into data careers, often overlapping in skills but serving different industry needs.

What are popular job titles related to Data Science Fall Internship jobs in Ontario? For Data Science Fall Internship jobs in Ontario, the most frequently searched job titles are:
What cities in Ontario are hiring for Data Science Fall Internship jobs? Cities in Ontario with the most Data Science Fall Internship job openings:
Infographic showing various Data Science Fall Internship job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $77,358 per year, or $37.2 per hour.

Salesforce QA & Data Analyst Co-Op

Semtech

Burlington, ON

Full-time

Posted 23 days ago


Job description

Location: Burlington, CAN

Job Summary:
This is a 12-16 month paid co-op or internship placement within Semtech's Revenue Operations team. This placement is a deliberate investment in your growth. You will build real, marketable experience working inside a global semiconductor company's Salesforce platform, testing, validating data, and documenting the systems that power a worldwide sales organization. Over the course of the placement, as you develop platform knowledge and business context, you will take on increasing responsibility.


Semtech operates two Salesforce Sales Cloud orgs supporting multiple global business units and a partner portal network. We are also expanding our data infrastructure to connect Salesforce with broader enterprise systems. You will play an active role in validating the data flowing through those .


Responsibilities:

Testing & Quality Assurance:

  • Design and build a comprehensive library of test scenarios covering key Salesforce objects and business processes - Accounts, Contacts, Opportunities, Quotes, Design Registrations, Design Wins, Cases, and partner portal interactions.
  • Execute test scenarios for every change, enhancement, or new feature deployed to our Salesforce orgs; document results and flag defects with clear reproduction steps.
  • Build and maintain reusable UAT templates that can be applied consistently across projects, creating test coverage that is repeatable and scalable as the team grows.
  • Collaborate with Salesforce BAs, Administrators and Developers to triage and validate defect fixes prior to production deployment.

Data Validation & Integration Testing:

  • Support testing and validation of data flowing between Salesforce and connected enterprise systems, verifying field-level accuracy, record completeness, and data integrity across platforms.
  • Write and run SOQL queries to investigate data quality issues, confirm expected values, and support ad hoc analysis requests.
  • Identify and document data anomalies, mismatches, or gaps between Salesforce and downstream systems; escalate findings with clear evidence and context.
  • Identify and flag duplicate, incomplete, or incorrectly formatted records across key Salesforce objects.

Technical & Process Documentation:

  • Document current-state business processes and Salesforce object configurations in clear, structured formats usable for onboarding, training, and future project planning.
  • Create and maintain field-level data dictionaries for key Salesforce objects, capturing field purpose, data type, population logic, and downstream dependencies.
  • Produce process maps and workflow diagrams that illustrate how data moves through Salesforce and into connected systems.
  • Document test plans, test cases, and defect logs in a structured format that supports team review and future reference.


Learning & Business Development:

  • Develop a working understanding of Semtech's global semiconductor sales model - including accounts, opportunities, design registrations, design wins, and distributor channel structures.
  • Work closely with the Revenue Operations and Salesforce Administration team to absorb platform knowledge and business context.

Minimum Qualifications:

  • Currently enrolled in a co-op or internship-eligible program at an Ontario university - programs in Business, Computing, Information Systems, Data Science, or a related discipline are a strong fit.
  • Completed at least one full year of study; Year 2 or Year 3 students preferred.
  • Eligible for a 12-16 month work term through your university's co-op or internship program.
  • Hands-on experience writing SQL or similar query language to investigate or validate data - coursework counts.
  • Comfortable working with data: spotting patterns, investigating anomalies, and communicating what you found clearly.
  • Strong written communication - able to document a technical process in plain language that a nontechnical reader can follow.
  • Detail-oriented and methodical.
  • Curious and self-directed.


Desired Qualifications:

  • Any exposure to Salesforce as a user, administrator, or in coursework.
  • Familiarity with data integration concepts.
  • Experience writing structured test cases or working within any QA or testing framework.
  • Experience producing technical documentation such as data dictionaries, process maps, or field mapping specs.

What you'll gain

  • Hands-on Salesforce platform experience across two live enterprise org.
  • Real exposure to a global semiconductor business and how enterprise sales data flows across CRM and connected business systems.
  • A portfolio of documented test libraries, data dictionaries, and process maps you built and own.
  • Mentorship from an experienced Salesforce administration and operations team.
  • Support toward Salesforce Administrator certification if pursued during the placement.


All duties and responsibilities are essential job functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities.

We are proud to be an EEO employer M/F/D/V. We maintain a drug-free workplace.

We may leverage Artificial Intelligence (AI) tools to enhance efficiency during candidate screening, assessment, and recruitment. Final hiring decisions remain with our Hiring Teams, not AI systems.

A reasonable estimate of the pay range for this position is $26 - $28.5 per/hr. There are several factors taken into consideration in determining base salary, including but not limited to: job-related qualifications, skills, education and experience, as well as job location and the value of other elements of an employee's total compensation package.