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

Royal Bank of Canada

Staff Data Engineer

Toronto, ON

Collaborate with data scientists, process engineers, and business stakeholders on requirement ... Data Analyst Associate or similar) What's in It for You? We thrive on the challenge to be our best ...

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 ...

ShyftLabs

Associate AI Engineer

Toronto, ON · Hybrid

CA$60K - CA$80K/yr

The Opportunity ShyftLabs is looking for an Associate AI Engineer (New Grad) to join our growing ... Bachelor's degree in Computer Science, Software Engineering, Data Science, AI, or a related field

Scotiabank

Associate Data Engineer

Toronto, ON

Purpose Contributes to the overall success of the Data Engineering Team under GOCT Solution ... Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent ...

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Data Science Associate information

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.

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 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 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 advance into more specialized roles.

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:

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 August 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 84% In-person, 11% Hybrid, and 5% Remote job distribution.

Associate Director/Director - Tech Consulting (Pharma/Lifesciences)

Tiger Analytics Inc.

Toronto, ON

Full-time

Posted 21 days ago

Job description

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for highly experienced and strategic leader to drive Commercial Data and Analytics initiatives.

RESPONSIBILITIES:

    • Data Analytics & Strategy: Lead the application of the latest data science techniques and advanced analytics approaches to solve complex business problems in the Pharma and Life Science domain.
    • Stakeholder & Solution Design: Work directly with client stakeholders to translate high-level business problems into detailed, high-level analytics solution designs.
    • Leadership & Execution: Lead strategic efforts in omni-channel analytics, helping the business optimize its marketing, sales, and digital engagements across various touch points in the commercial pharmaceutical sector.
    • Business Intelligence (BI) & Analytics: Lead the design and delivery of advanced analytical and Business Intelligence (BI) products, focusing on metrics design, reporting, and leveraging data best practices to drive informative decisions.
    • Data Management & Engineering (DE): Oversee and guide data architectures, ensuring a strong emphasis on data quality, data integrity, and compliance with commercial data management frameworks.
    • Commercial Expertise: Apply extensive experience in core commercial pharma areas such as omni-channel strategy, customer journey mapping, and marketing effectiveness.
    • Client Engagement: Serve as a key analytics consulting leader, working closely with senior client stakeholders to understand business requirements, design solutions, and drive cross-functional collaboration.

Requirements

  • 12-16 years of professional work experience with at least 8 years in data analytics
  • Ability to engage with executive/VP level stakeholders from client's team to translate business problems to high level analytics solution approach
  • Solid understanding of statistical and machine learning algorithms
  • Strong project management and team management skills and ability to work with global teams.
  • Fluency and extensive working experience with various pharmaceutical data sources, including: Claims and Prescriber data (e.g., IQVIA Xponent, Plantrak, LAAD, PE), Execution data (e.g., Veeva CRM), Real-World Data (RWD) sources such as TriNetX, Flatiron, Optum, and Komodo. Specialty Pharmacy data and Payer Formulary (MMIT) data.
  • Graduate in Business Analytics or MBA or equivalent work experience

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

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