Skip to main content

How Much Do Data Scientists Make in Canada 2026 | Data Science Salaries

Updated

Data science in Canada has evolved from a niche role to a mainstream career path, and the compensation reflects it. The field spans a wide range — from data analysts doing SQL queries and dashboards at $55,000-$75,000, to machine learning engineers building production AI systems at $150,000-$200,000+. The biggest salary drivers are your specific technical skills (ML engineering and MLOps pay more than pure analytics), the industry you work in (tech and finance pay the most), and whether you’re at a Canadian company or a US company with Canadian offices. The latter distinction is key: US-headquartered tech companies routinely pay 30-50% more for the same roles in Toronto or Vancouver.

Data Science Salary by Experience

LevelData AnalystData ScientistML Engineer
Junior (0-2 years)$50,000-$68,000$65,000-$88,000$72,000-$95,000
Mid-level (2-5 years)$65,000-$85,000$90,000-$130,000$100,000-$145,000
Senior (5-8 years)$78,000-$100,000$120,000-$165,000$135,000-$180,000
Staff/Principal (8+ years)$90,000-$120,000$150,000-$210,000$160,000-$230,000+
Director/Head of Data$160,000-$250,000$170,000-$260,000+

Salary by Province

Toronto and Vancouver lead data science pay, driven by concentrations of tech companies, banks, and US-headquartered firms. Montreal has a uniquely strong AI research ecosystem (MILA, Element AI alumni, university labs) that supports mid-range salaries but world-class research opportunities. Calgary and Ottawa are smaller markets but growing.

ProvinceMid-Level Data ScientistSenior Data Scientist
Ontario (Toronto)$95,000-$135,000$130,000-$180,000
British Columbia (Vancouver)$90,000-$130,000$125,000-$175,000
Quebec (Montreal)$80,000-$115,000$110,000-$155,000
Alberta (Calgary)$85,000-$120,000$115,000-$160,000
Ontario (Ottawa)$85,000-$120,000$115,000-$160,000
Manitoba$75,000-$100,000$95,000-$135,000
Saskatchewan$72,000-$98,000$95,000-$130,000
Nova Scotia (Halifax)$70,000-$95,000$92,000-$130,000
Remote (US company, Canadian employee)$110,000-$170,000$155,000-$230,000+

Salary by Industry

IndustryMid-LevelSeniorNotes
Big tech (Google, Amazon, Meta, etc.)$120,000-$170,000$170,000-$260,000+Includes equity/RSU
Fintech/startup (funded)$100,000-$145,000$140,000-$200,000Often includes equity
Banking/financial services$90,000-$130,000$125,000-$175,000Strong benefits, stable
Consulting (McKinsey, Deloitte, etc.)$85,000-$125,000$120,000-$170,000Bonus-heavy
Telecom (Bell, Rogers, Telus)$82,000-$115,000$110,000-$155,000Stable, good benefits
Insurance$80,000-$112,000$105,000-$150,000Actuarial overlap
E-commerce/retail$80,000-$115,000$110,000-$155,000Product analytics focus
Healthcare/biotech$78,000-$110,000$105,000-$150,000Growing rapidly
Government/public sector$70,000-$100,000$95,000-$130,000Best pension/benefits
Energy/utilities$80,000-$110,000$105,000-$145,000Alberta-heavy

Total Compensation at Tech Companies

At US-headquartered tech companies, base salary is only part of the picture. Total compensation (TC) includes equity (RSUs), bonus, and sometimes signing bonuses. This can add 20-60% on top of base salary.

LevelBase SalaryEquity (RSU/year)BonusTotal Comp
Junior (L3/IC1)$80,000-$100,000$10,000-$30,000$5,000-$10,000$95,000-$140,000
Mid (L4/IC2)$110,000-$140,000$25,000-$60,000$10,000-$20,000$145,000-$220,000
Senior (L5/IC3)$140,000-$175,000$50,000-$100,000$15,000-$30,000$205,000-$305,000
Staff (L6/IC4)$170,000-$210,000$80,000-$160,000$20,000-$40,000$270,000-$410,000

Note: These figures represent US-headquartered companies with Canadian offices (Toronto/Vancouver). Canadian-headquartered companies typically pay 30-50% less in total compensation.

Salary by Role/Title

RoleSalary RangePrimary Skills
Data analyst$50,000-$85,000SQL, Excel, Tableau/Power BI, basic Python
Business intelligence analyst$60,000-$95,000SQL, dashboarding, ETL, stakeholder reporting
Data scientist$75,000-$150,000Python/R, statistics, ML, experimentation
Machine learning engineer$85,000-$180,000Python, ML frameworks, MLOps, production systems
AI/ML research scientist$100,000-$200,000+Deep learning, NLP, computer vision, publications
Data engineer$80,000-$150,000SQL, Spark, Airflow, cloud (AWS/GCP), data pipelines
MLOps engineer$90,000-$155,000Kubernetes, CI/CD, model deployment, monitoring
Analytics engineer$80,000-$130,000dbt, SQL, data modelling, Snowflake/BigQuery
NLP/LLM engineer$100,000-$180,000+Transformers, fine-tuning, prompt engineering, RAG
Head of Data / VP Data$160,000-$280,000Leadership, strategy, cross-functional influence

Education Paths

PathDetailsTypical Outcome
B.Sc. (CS/Stats/Math) + experience4 years + 2-3 years workData analyst or junior data scientist
M.Sc. (CS/Stats/Applied Math)2 years post-undergradData scientist or ML engineer
Ph.D. (ML/Stats/CS)4-6 years post-undergradResearch scientist, senior DS at tech companies
Bootcamp + quantitative degree3-6 monthsData analyst (entry level)
MBA + analytics focus2 yearsAnalytics/product analytics, management track

Education Costs

ProgramApproximate Cost
B.Sc. (4 years, Canadian university)$24,000-$50,000
M.Sc. (2 years, often funded)$10,000-$30,000 (many have stipends)
Ph.D. (4-6 years, funded)Typically $0 + $20,000-$30,000/year stipend
Data science bootcamp$8,000-$18,000
Online certificates (Coursera, etc.)$500-$5,000

Key Skills and Their Pay Premium

SkillImpact on Salary
Python (advanced)Baseline requirement
SQL (advanced)Baseline requirement
Machine learning (production)+$15,000-$30,000
Deep learning / NLP+$20,000-$40,000
Cloud platforms (AWS/GCP/Azure)+$10,000-$20,000
MLOps / model deployment+$15,000-$30,000
LLM/GenAI experience+$20,000-$50,000
Spark / distributed computing+$10,000-$20,000
Communication / stakeholder managementAccelerates promotion

Job Outlook

The data science field is in a period of maturation. The initial hype wave has settled, and employers now have clearer expectations for different levels (data analyst vs. data scientist vs. ML engineer). Entry-level competition is stiff — many candidates have degrees and bootcamp certificates but lack production experience. However, demand for experienced practitioners with ML engineering skills, especially in generative AI and LLMs, has surged. The Canada-specific advantage is the strong AI research ecosystem (MILA in Montreal, Vector Institute in Toronto, Amii in Edmonton) which attracts investment and creates a pipeline of high-quality roles.

FactorStatus
Overall demandStrong — especially for senior and ML-focused roles
Entry-level competitionHigh — many candidates, fewer junior openings
Hottest skills (2026)LLMs, RAG systems, MLOps, real-time ML
Remote workCommon — many roles fully remote
Canada vs US pay gap30-50% for same role; narrowing slowly
AI research ecosystemWorld-class (MILA, Vector, Amii)
Immigration pathwayStrong — data science roles qualify for Global Talent stream

→ Back to: Canadian Income Guide