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

SOTI Inc

Associate Director, Data Sciences

Mississauga, ON · On-site

$130 - $160/hr

Associate Director, Data Sciences Location: Mississauga, Ontario, Canada. Work Model: Hybrid. Role ... Spearhead the Data Science function responsible for developing and delivering AI‑driven ...

BMO Capital Markets

Associate, Data Scientist

Toronto, ON

CA$90K - CA$120K/yr

D. in Computer Science, Mathematics, Physics, or a related quantitative field (focus on finance, economics, or operations research preferred). Minimum 3 years of experience in data science or machine ...

Accenture

AI Architect, Manager

Toronto, ON · Remote

You're likely to be a MSFT Certified Data Science Associate and you have been in a similar professional position for around five to seven years. * Cross talent community skillset, one resource that ...

Walmart

Senior, Data Scientist

Mississauga, ON · On-site

CA$91K - CA$126K/yr

... science solutions. * Strong communication and storytelling skills, with the ability to explain ... Walmart will accommodate the disability-related needs of applicants and associates as required by ...

PwC

Azure Data Consultant, Senior Associate

Toronto, ON · Hybrid

CA$84K - CA$134K/yr

Collaborate with data scientists, analysts, and business stakeholders to deliver robust solutions ... Azure Data Engineer Associate (DP-203); Microsoft Certified: Fabric Analytics Engineer Associate;

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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.

Is 40 too late for data science?

Age is not a barrier to becoming a data science associate; many professionals transition into data science later in their careers. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Is an Associates in data science worth it?

An associate's degree in data science can provide foundational skills in data analysis, programming, and statistics, which may help entry-level candidates qualify for junior data science roles. However, many employers prefer candidates with a bachelor's degree or higher, and practical experience or certifications in tools like Python, R, or SQL can enhance job prospects. The value depends on career goals and the specific requirements of potential employers.

What can I do with an associate's degree in data science?

A Data Science Associate with an associate's degree can work as a data analyst, supporting data collection, cleaning, and basic analysis using tools like Excel, SQL, and Python. They often assist in generating reports, visualizations, and insights under supervision, and may pursue certifications to enhance their skills for more advanced roles.

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 is the role of an associate data scientist?

An associate data scientist supports data analysis and modeling tasks by cleaning and processing data, developing algorithms, and creating visualizations. They often work under supervision to assist in building predictive models and may use tools like Python, R, or SQL to analyze data and generate insights.

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

Associate Director, Data Sciences

SOTI Inc

Mississauga, ON • On-site

$130 - $160/hr

Other

Posted 6 days ago

Job description

Associate Director, Data Sciences

Location: Mississauga, Ontario, Canada. Work Model: Hybrid.

Role Overview

Lead the strategic direction of AI and data intelligence initiatives, transforming complex data challenges into enterprise-wide innovations that drive competitive advantage and long‑term growth.

Responsibilities
  • Spearhead the Data Science function responsible for developing and delivering AI‑driven capabilities across SOTI’s product portfolio.
  • Define, execute, and continually refine the enterprise‑wide AI strategy, integrating machine learning, advanced analytics, and data intelligence to optimize product capabilities, enhance customer outcomes, and boost operational efficiency.
  • Stay current with emerging developments in artificial intelligence and machine learning and translate them into practical innovations that strengthen SOTI’s competitive position.
  • Partner closely with Product Management and Development teams to embed predictive insights, anomaly detection, and automation into SOTI One product constituents.
  • Guide and mentor a team of data scientists and ML engineers, fostering a culture of experimentation, innovation, and delivery excellence.
  • Drive the development of scalable machine learning pipelines and data platforms capable of processing large‑scale device telemetry and operational data.
  • Collaborate with engineering teams to operationalize models in production environments using modern MLOps practices.
  • Proactively identify and prioritize AI opportunities through market analysis and stakeholder alignment, leveraging analytics for advanced product intelligence, predictive maintenance, anomaly detection, and actionable operational insights that deliver measurable ROI for enterprise customers.
  • Advise executive leadership on AI trends, risks, and investment priorities, crafting roadmaps that align data science initiatives with SOTI’s long‑term business goals and regulatory landscape.
Qualifications
  • Graduate degree in computer science, software engineering, applied mathematics, data science, statistics, or related field.
  • 10+ years in analytics, data science, or related fields, with 5+ years in senior leadership roles overseeing cross‑functional teams and strategic AI implementations.
  • Strong communication and leadership skills with the ability to influence senior stakeholders and translate complex analytical concepts into product value.
  • Proven experience delivering machine learning capabilities within production SaaS or enterprise software products.
  • Strong understanding of statistical modeling, machine learning, and modern AI techniques, including supervised learning, anomaly detection, time‑series analysis, and deep learning.
  • Demonstrated experience in strategic planning, including developing AI roadmaps, budgeting for data science initiatives, and evaluating partnerships or acquisitions to accelerate innovation.
  • Experience working with large‑scale data platforms and cloud environments such as Microsoft Azure or Amazon Web Services.
  • Experience building production‑grade ML pipelines, including model training, deployment, monitoring, and lifecycle management.
  • Experience working with large telemetry datasets, distributed data processing systems, or real‑time analytics platforms is considered an asset.
Benefits
  • Opportunity for personal growth, continuous innovation, and a fun, collaborative culture.
  • Fast‑paced environment with global reach that encourages you to make an impact.
  • Exposure to leading‑edge technologies and emerging innovations through partnerships with industry giants.
Equal Opportunity and Accessibility

We are proud to be an equal‑opportunity workplace. We are committed to providing accessible employment practices in compliance with the Human Rights Code and the Accessibility for Ontarians with Disabilities Act (AODA). If you require accommodation during any stage of the recruitment process, please notify People & Culture at careers@soti.net.

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