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Data Science Jobs in Toronto, ON (NOW HIRING)

The Data Engineer / Data Science Specialist builds and automates the data foundation that the Engine and its initiatives rely on: cloud-based data pipelines, lake/Lakehouse structures, analytics ...

Reporting to the Director, Data Science, as a Senior Data Scientist you will focus on supporting Canadian business units in accelerating the growth and application ofadvancedanalytics in driving ...

Data Scientist

Woodbridge, ON ยท On-site

CA$85K - CA$115K/yr

Data Science and Analytics Location: 6300 Steeles Ave West, Woodbridge Total Potential Compensation: $85,000-$115,000 Position Summary: The successful candidate will assist in leveraging customer ...

Data Scientist

Toronto, ON

CA$68K - CA$100K/yr

Ensure the accuracy and reliability of data science models, conduct peer reviews of AI and other predictive models AI and Data Science research and development * Research, code, develop and implement ...

Provide statistical expertise and develop data science solutions to Pharma technical operations, including process development, analytical method development, commercial manufacturing and quality ...

Data Scientist

Toronto, ON ยท Remote

  • Medical

  • Retirement

Follow advancements in data science, machine learning, and healthcare analytics Qualifications * Commitment to understanding customer needs and helping them achieve goals * Creative mindset with a ...

About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make ...

The Mastercard Security Solutions Data Science team is seeking a Director of Data Science to lead the development and delivery of machine learning models focused on Anti-Money Laundering and crypto ...

Senior Data Scientist

Toronto, ON ยท Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You will lead and deliver complex data science initiatives, guide experimentation with new AI capabilities, and transform large, diverse datasets into actionable recommendations and scalable AI ...

Collaborate with cross-functional teams to translate business problems into robust data science solutions. * Support best practices in model development, experimentation, documentation, and data ...

Collaborate with cross-functional teams to translate business problems into robust data science solutions. * Support best practices in model development, experimentation, documentation, and data ...

About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make ...

Data Scientist - Hybrid

Oakville, ON ยท Hybrid

  • Retirement

  • PTO

Degree in a STEM discipline (Data Science, Statistics, Computer Science, or a related quantitative field); a Master's or PhD is preferred but not required. * 3+ years of data science experience ...

Data Scientist 2

Toronto, ON ยท Hybrid

CA$84K - CA$126K/yr

  • Medical

  • Retirement

Participate in the data science lifecycle from understanding the business problem, to data extraction, to model development, to production deployment and change management * Perform data extraction ...

Data Science and Analytics Location: 6300 Steeles Ave West, Woodbridge Total Potential Compensation: $120,000-$165,000 Position Summary: The successful candidate will assist in leveraging customer ...

Senior Data Scientist

Toronto, ON ยท Hybrid

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

D. degree in Computer Science, Data Science, Statistics, Engineering, Physics, or a related quantitative field. * 5+ years of hands on industry experience in developing probabilistic models ...

Showing results 21-40

Data Science information

See Toronto, ON salary details

$22.4K

$111.5K

$200.9K

How much do data science jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data science in Toronto, ON is $111,528.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,077.00 and $153,648.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.

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 jobs in Toronto, ON?

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

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

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

Infographic showing various Data Science job openings in Toronto, ON as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $111,528 per year, or $53.6 per hour.

RQ00745-Data Science Developer

Source Code

Toronto, ON โ€ข On-site

Full-time

Posted 20 days ago


Job description

RQ00745 -Requisition TitleData Science Developer

Location: Toronto (661 University Ave, Suite 1701, Toronto, ON M5G 1M1)

Duration: 6 months + possible extention

Position Summary

Public Health Ontario (PHO) is building provincial enhanced analytics capability and infrastructure that turns public health data into timely analytics, surveillance, and decision support. The Data Engineer / Data Science Specialist builds and automates the data foundation that the Engine and its initiatives rely on: cloud-based data pipelines, lake/Lakehouse structures, analytics models, and visualizations.

The role combines two functions. As a Data Engineer, it automates the data pipeline for analytic products and advanced analyses. As a Data Science Specialist, it helps identify and prioritize use cases and integrate AI techniques (machine learning, NLP) into PHO's work, increasing capacity for modelling, forecasting, and scenario analysis. The role supports both foundational capability/infrastructure work and HealthMap data ingestion and aligns with and advances the Public Health Data Utility (PHDU) on PHO's Azure platform.

Key Responsibilities

  • Participate in product teams to analyze system requirements, and architect, design, code, and implement cloud-based data and analytics products that conform to standards.
  • Design, create, and maintain cloud-based data lake and Lakehouse structures, automated data pipelines, analytics models, and visualizations (dashboards and reports).
  • Liaise with IT colleagues to implement products, conduct reviews, resolve operational problems, and support business partners in the effective use of cloud-based data and analytics products.
  • Analyze complex technical issues, identify alternatives, and recommend solutions.
  • Prepare and conduct knowledge transfer.
  • Automate the data pipeline for analytic products and advanced analyses, including ingestion, ETL, and production for the foundational capability and for HealthMap (DLSPH model data).
  • Help identify and prioritize analytic use cases and integrate AI techniques (machine learning, NLP) into PHO's work.
  • Increase PHO's capacity for modelling, forecasting, and scenario analysis.
  • Build on and advance the PHDU and PHO's Azure data and analytics platform; support data acquisition through data-sharing and governance processes where required.
  • Document methods and transfer knowledge to PHO staff so the pipeline and capability can be sustained beyond the engagement.

Key Deliverables

  • Automated data pipelines and cloud data lake / Lakehouse structures supporting the capability and HealthMap.
  • Analytics models and visualizations (dashboards and reports) conforming to standards.
  • Prioritized AI / ML use cases and supporting models (forecasting, scenario analysis).
  • Knowledge-transfer documentation and sessions for PHO technical staff.

Required Skills

  • Experience with multiple cloud-based data and analytics platforms and coding / programming / scripting tools to create, maintain, support, and operate cloud-based data and analytics products.
  • Experience designing, creating, and maintaining cloud-based data lake and Lakehouse structures, automated data pipelines, analytics models, medallion architecture, and visualizations (dashboards and reporting) in real-world implementations.
  • Deep experience with modern technology stacks: Azure Storage, Azure Data Lake, Azure Databricks Lakehouse, and Azure Synapse. Power BI, Python, SQL, Azure Databricks, and Azure Data Factory.
  • Experience assessing client information-technology needs and objectives.
  • Experience problem-solving to resolve complex, multi-component failures.
  • Experience preparing knowledge-transfer documentation and conducting knowledge transfer.
  • A team player with a track record for meeting deadlines.

Desirable Skills

  • Written and oral communication skills to participate in team meetings, write and edit systems documentation, prepare and present written reports on findings and alternative solutions, and develop guidelines / best practices.
  • Interpersonal skills to explain and discuss the advantages and disadvantages of various approaches.
  • Experience conducting knowledge-transfer sessions and building documentation for technical staff on architecting, designing, and implementing end-to-end data and analytics products.

Expected Skills

  • Be an advanced professional able to apply concepts, practices, and procedures in practice.
  • Work with minimal direction and lead and train others in technical components and concepts.
  • Plan, lead, and deliver complex deliverables that provide options for decisions within the organization.
  • Bring a high level of expertise in the required skill set, specialized in the technical area, and provide specific advisory support as required.

AI Disclaimer: Source Code may use artificial intelligence (AI) tools to assist in certain aspects of its recruiting and business operations.

Note: The higher end of the range is intended for absolutely exceptional candidates who meet all must-have requirements and most or all nice-to-have qualifications. The client will evaluate candidates based on both rate expectations and overall skill set when shortlisting.

INCORPORATED RATE RANGE (7.25 billable hours per day)

  • $68.55/hr - $82.26/hr Inc.

T4 RATE RANGE (7.25 billable hours per day)

  • $54.84/hr - $65.81/hr T4