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Causal Inference Jobs in Ontario (NOW HIRING)

Fullscript

Senior Customer Insights Analyst

Toronto, ON · Remote

CA$90K - CA$115K/yr

Familiarity with experimentation, causal inference, cohort analysis, segmentation, or predictive modeling. * Experience influencing product roadmaps, CX strategy, or operational planning through ...

Td

Applied Machine Learning Scientist I

Toronto, ON · On-site +1

CA$105K - CA$125K/yr

Familiarity with causal inference or reinforcement learning Who We Are: TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches ...

Td

Applied Machine Learning Scientist II

Toronto, ON · On-site

CA$125K - CA$154K/yr

Familiarity with causal inference or reinforcement learning Who We Are: TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches ...

Td

Data Scientist III

Toronto, ON · On-site

CA$96K - CA$136K/yr

Apply statistical techniques to evaluate causal impact, quantify uncertainty, and validate business ... Strong foundation in statistical inference, hypothesis testing, regression, sampling methodologies ...

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All JobsCausal Inference JobsCausal Inference Jobs in Ontario

Causal Inference information

See Ontario salary details

$21K

$114.4K

$169.5K

How much do causal inference jobs pay per year?

As of Aug 7, 2026, the average yearly pay for causal inference in Ontario is $114,369.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $156,000.00 per year, depending on experience, location, and employer.

Is causal inference still relevant?

Causal inference is a vital skill for data analysts and researchers, as it helps determine cause-and-effect relationships in data. It remains highly relevant across industries such as healthcare, economics, and technology, especially with the increasing availability of large datasets and advanced statistical tools like R and Python. Professionals in this field are in demand for designing experiments, analyzing observational data, and informing decision-making processes.

What skills and qualifications are needed for a causal inference position?

Success in a Causal Inference role requires strong statistical knowledge, expertise in experimental and quasi-experimental methodologies, and advanced proficiency in programming languages like R or Python, typically acquired with an advanced degree in statistics, economics, data science, or a related field. Familiarity with specialized statistical software (such as Stata, SAS, or causal inference packages in R/Python), as well as experience with large datasets and machine learning tools, is highly valued. Excellent problem-solving abilities, clear communication, and collaboration skills are essential soft skills for effectively conveying complex findings to diverse teams. These competencies are critical to producing reliable insights that guide evidence-based decision-making in business, healthcare, or policy settings.

What jobs use causal inference?

Causal inference is used in various roles such as data scientist, epidemiologist, econometrician, and policy analyst. These jobs involve analyzing data to determine cause-and-effect relationships, often using statistical tools and programming languages like R or Python. Professionals in these fields work in industries like healthcare, finance, government, and technology to inform decision-making and policy development.

What are common challenges faced in a causal inference position?

Professionals in Causal Inference often encounter challenges such as dealing with confounding factors, addressing selection bias, and ensuring the validity of assumptions behind statistical models. They must carefully design experiments or leverage observational data while staying vigilant about potential data quality issues and model limitations. Collaboration with subject matter experts, data engineers, and business stakeholders is common to ensure accurate contextualization of results. Overcoming these challenges requires a mix of technical acumen and strong communication skills to translate complex analyses into actionable recommendations.

What is a causal inference?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.

What are popular job titles related to Causal Inference jobs in Ontario? For Causal Inference jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Causal Inference jobs in Ontario look for? The top searched job categories for Causal Inference jobs in Ontario are:
Causal Inference jobs near you
Infographic showing various Causal Inference job openings in Ontario as of August 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution, with an average salary of $114,369 per year, or $55 per hour.

Senior Customer Insights Analyst

Fullscript

Toronto, ON • Remote

CA$90K - CA$115K/yr

Full-time

Retirement, PTO

Re-posted 4 days ago

Job description

About Fullscript

We're an industry-leading health technology company on a mission to help people get better. We started in 2011 with one simple idea. Make it easier for practitioners to access the products they trust so they can deliver better care.

That simple idea grew into a platform that powers every part of care. Today, more than 125,000 practitioners use Fullscript for clinical insights, lab interpretations, patient analytics, education, and access to high-quality supplements. Over 10 million patients rely on Fullscript to stay connected to their care plans and follow through on treatment.

We build tools that make care smarter and more human. Tools that save time, simplify decisions, and help practitioners stay closely connected to the people they care for. When everything they need is in one place, they can focus on what matters most: helping people get better.

This is your invitation.

Bring your ideas, your grit, and your care for people.
Join us and shape the future of care.
The Opportunity

Customer Experience is one of the clearest signals we have into how practitioners and patients experience Fullscript.
Fullscript is looking for a Senior Customer Insights Analyst who can turn complex customer data into business insight that shapes CX strategy, product decisions, and operational priorities. In this role, you'll work across support data, product behavior, customer feedback, and voice-of-customer signals to identify what is working, what is breaking, and where Fullscript should focus next.

This is not a dashboard role. You'll define what needs to be understood, translate ambiguous problems into structured analysis, and deliver clear recommendations to senior leaders.

Reporting to the VP, Customer Experience, you'll partner closely with Product, Data, Engineering, Support, and Operations to turn customer insight into action.

What you'll do
  • Synthesize complex data across support, product usage, customer behavior, VOC, and operational workflows.
  • Identify systemic risks and opportunities across the practitioner and patient journey, not just isolated issues.
  • Translate ambiguous business questions into structured analysis, clear findings, and recommended actions.
  • Work directly with modern data warehouses.
  • Use AI-assisted tools to accelerate insight discovery, anomaly detection, and qualitative signal extraction.
  • Evolve VOC from a reporting function into a strategic capability that informs Product, CX, and Operations.
  • Build executive-ready narratives that connect customer impact, root cause, opportunity size, and business trade-offs.
What you bring to the table
  • 8+ years of experience in analytics, customer insights, product analytics, business intelligence, or data strategy.
  • Strong SQL skills and hands-on experience with modern cloud data warehouse tools such as Snowflake, BigQuery, Redshift, or similar tools.
  • Proven ability to use data to influence business decisions, not just produce reports.
  • Strong analytical judgment, including the ability to interpret messy or incomplete data in context.
  • Experience connecting qualitative and quantitative signals to uncover root causes and business impact.
  • Excellent executive communication and stakeholder management skills.
  • High autonomy, strong ownership, and the ability to define what should be analyzed, not just how.
Bonus if you have
  • Experience in healthcare technology, digital health, SaaS, marketplaces, e-commerce, or regulated environments.
  • Experience building or evolving a voice-of-customer program.
  • Experience analyzing unstructured feedback, support tickets, call transcripts, surveys, or product comments.
  • Experience using AI-assisted analysis for text synthesis, clustering, anomaly detection, or workflow automation.
  • Familiarity with experimentation, causal inference, cohort analysis, segmentation, or predictive modeling.
  • Experience influencing product roadmaps, CX strategy, or operational planning through insights.
What we can offer you
  • Salary range: $90,000 to $115,000 CAD
  • Remote-first flexibility to work where you work best, with Ottawa, Toronto, or Calgary preferred for this role.
  • Flexible PTO and competitive pay, because work-life balance matters
  • RRSP/401k match and stock options to invest in your future
  • Premium benefits package with customizable coverage, paramedical services, and an HSA.
  • Fullscript discounts to save on high-quality wellness products
  • Continuous learning opportunities to grow your skills and career

Fullscript shares salary ranges to support transparency and help candidates make informed decisions. The range shown reflects base salary only and does not include stock options, wellness stipends, or other benefits that are part of Fullscript's total rewards package.

Final compensation depends on experience, skills, and location. We review pay regularly to stay aligned with market data and internal equity. Benefits and total rewards may vary by region.

Why Fullscript

Great work happens when people feel supported, trusted, and inspired. At Fullscript, we stay curious and keep finding smarter ways to make care better. We grow together, take on new challenges, and focus on impact. We put people first, work as a team, and leave egos at the door.

What to Know Before You Apply

We're grateful for the interest in joining Fullscript. To make sure your application reaches our hiring team, please apply directly through our careers page.

A quick note: Due to the high volume of applications, we're not able to respond to phone or email inquiries about application status. If there's a match, our team will reach out directly.

Fullscript is an equal opportunity employer committed to creating an inclusive workplace. Accommodations are available upon request at [email protected].

All offers are contingent on successful background checks conducted in compliance with federal, state, and provincial laws.

We use AI tools to support parts of the hiring process, including screening and reviewing responses. Final hiring decisions are always made by people and follow all applicable privacy and employment laws in Canada and the U.S.

Learn More
www.fullscript.com
@fullscriptHQ on instagram
@fullscript on YouTube
FullScript on LinkedIn
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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