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Data Science Associate Jobs in Toronto, ON (NOW HIRING)

TransUnion

Principal, Fraud Analytics

Burlington, ON · On-site

Data Science & Modeling : Oversee the development of machine learning models, rules engines, and ... We strive to build an environment where our associates are in the driver's seat of their ...

BMO Capital Markets

Associate, Data Engineer

Toronto, ON · On-site

CA$90K - CA$120K/yr

  • Medical

  • Life

  • Retirement

You will collaborate with AI engineers and data scientists to deliver high-quality, data-centric solutions that empower business decisions. Our Team The Data Cognition Team (DCT) at BMO Capital ...

GFL Environmental

Data Engineer

Vaughan, ON

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Work closely with data scientists, business analysts, and other stakeholders to understand data ... AWS Certified Solutions Architect - Associate or Professional. What We Offer Why join us? We ...

Accenture

AI Advisory Lead

Toronto, ON · On-site

We're the world's largest team of data scientists and experts in machine learning and AI. A great ... As an Associate Director, you will coach and mentor up-and-coming leaders, guide diverse multi ...

Bits In Glass

Databricks Solution Architect

Toronto, ON · Remote

Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI ... Databricks GenAI Engineer Associate certification. * Exposure to enterprise engagement cycles and ...

Bits In Glass

Databricks Solution Architect

Toronto, ON · Remote

Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI ... Databricks GenAI Engineer Associate certification. * Exposure to enterprise engagement cycles and ...

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 Toronto, ON

Data Science Associate information

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.

What can I do with a data science associate?

A data science associate typically supports data analysis, data cleaning, and model development using tools like Python, R, or SQL. They may assist in preparing reports, visualizations, and insights for decision-making, often working under the guidance of senior data scientists or analysts.

What is a data science associate?

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?

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 Toronto, ON?

The most popular types of Data Science jobs in Toronto, ON are:

What are popular job titles related to Data Science Associate jobs in Toronto, ON?

For Data Science Associate jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Data Science Associate jobs in Toronto, ON look for?

The top searched job categories for Data Science Associate jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Data Science Associate jobs?

Cities near Toronto, ON with the most Data Science Associate job openings:

Data Science Associate jobs near you
Infographic showing various Data Science Associate job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Data Development Intern

Environics Analytics

Toronto, ON

$30/hr

Full-time, Internship

Posted 4 days ago

Job description

Role Objective:

The Data Development Intern plays a central role in building, maintaining, and modernizing the data infrastructure that powers Environics Analytics' core demographic and behavioural data products. The Data Development team works across a wide range of data sources, including Statistics Canada, IRCC, CRA, and third-party survey data, applying rigorous ETL, quality control, and modeling pipelines to produce market-ready outputs from national to small-area geographies.


You'll design and implement automated data pipelines in SQL and Python, support the migration of legacy workflows to modern architecture (including the team's move to Snowflake), and contribute to quality control systems that ensure the accuracy and consistency of our data products across vintages. This is a hands-on role with real ownership of production code, and strong performers will be well positioned for a full-time Data Engineer role on the team.


What You'll Do:

  • Design, build, and maintain automated data pipelines for ETL, modelling, and quality control across demographic data products.
  • Help migrate and refactor legacy workflows into SQL (T-SQL) and Python, improving scalability, maintainability, and version control.
  • Develop stored procedures, temp table-based workflows, and batch scripts to support large-scale data transformation.
  • Build automated QC checks and validation logic to catch anomalies and inter-vintage inconsistencies early in the pipeline.
  • Collaborate with data developers, Research Associates, and Technical Leads to translate data product methodology into reliable, repeatable code.
  • Present design approaches before building, validate results after, and participate in code reviews.
  • Use Azure DevOps and Git for version control and work item tracking; maintain documentation on SharePoint.
  • Investigate and prototype new tools, libraries, or pipeline architectures, including Snowflake-native approaches, that improve team efficiency or product quality.
  • Use AI coding tools (e.g., GitHub Copilot) as a core part of daily development to accelerate scripting, refactoring, and code review.
  • Apply AI-assisted approaches to documentation and QC, such as generating test cases, drafting validation logic, or summarizing pipeline behaviour.
  • Critically evaluate AI-generated code and output, verifying correctness and understanding the underlying SQL/Python well enough to own what ships.


What You'll Learn:

  • Practical, production experience in data engineering, automation, and AI-assisted development.
  • Exposure to large-scale demographic, financial, and behavioural datasets.
  • Insight into the full product development lifecycle at a leading data and analytics firm.
  • Modern cloud data warehousing (Snowflake) alongside traditional SQL Server workflows.
  • Agile development, version control, and code review practices.
  • Best practices in quality control and data integrity at scale.


Qualifications:

Education

Enrolled in or recently completed a graduate program (Master's) in Computer Science, Data Science, Statistics, Geography, Engineering, or a related quantitative field. Undergraduate candidates with strong relevant experience will also be considered.

Experience

  • Prior experience (coursework, research, co-op, or work) in data engineering, data analysis, or software development.
  • Comfort working with large-scale structured datasets (millions of rows across related tables).

Technical Skills

  • Strong SQL, including window functions and set-based transformation logic; T-SQL experience is a plus.
  • Proficiency in Python for data processing and automation, including pandas.
  • Experience building or contributing to multi-step ETL pipelines.
  • Comfort working in VS Code, Jupyter Notebook, and/or SQL Server Management Studio.
  • Experience with Git and a willingness to learn Azure DevOps.
  • Comfort using AI coding tools (e.g., GitHub Copilot) as part of your regular workflow.

Bonus Skills

  • Familiarity with Snowflake or other cloud data warehousing.
  • Familiarity with ETL processes and APIs.
  • Exposure to geospatial data or Canadian census geographies (e.g., DA, CT, CSD, CMA).
  • Familiarity with dashboards, data visualization, or statistical concepts (imputation, aggregation, index construction).
  • Exposure to workflow orchestration tools (e.g., Airflow) or distributed computing (e.g., Dask).

Personal Attributes

  • Strong problem-solving skills and eagerness to learn; comfortable identifying root causes and proposing systematic fixes.
  • Detail-oriented, with good documentation and communication habits.
  • Collaborative and open to feedback; comfortable working in a multidisciplinary team of researchers and data professionals.
  • Able to clearly communicate technical findings to both technical and non-technical stakeholders.


About Environics Analytics

Environics Analytics (EA) is a marketing services company that specializes in geodemographic-based segmentation, site evaluation modelling, and custom analytics.

EA is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you require any accommodation to participate in the hiring process, please note the request in your application. We welcome people of all abilities.


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