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Behavioural Science Jobs in Quebec (NOW HIRING)

Celltrion Healthcare Canada Ltd.

$90 - $120/hr

... Behavioural Competencies & Skills * Demonstrate critical leadership capabilities including ... Ability to learn and convey medical/scientific information to healthcare professionals and decision ...

Accenture

Workplace Advisory Consultant

Quebec, QC · Hybrid

CA$96K - CA$114K/yr

Bachelor's degree, preferably in Behavioral Science, Psychology, or a related field * 2+ years' experience to survey platforms and analytics tools (Viva Glint strongly preferred) * 2+ years ...

Galderma

Material Scientist

Baie-d'urfe, QC · On-site

Analyze and characterize materials and their chemical composition and behavior * Understand ... MSc or PhD in Material Science, Chemistry, or related field * 3-8+ years in pharma, biotech ...

Galderma

Material Scientist

Baie-d'urfe, QC

We deliver an innovative, science-based portfolio of premium flagship brands and services that span ... Analyze and characterize materials and their chemical composition and behavior * Understand ...

LawZero

Senior ML Research Scientist

Montreal, QC

Advanced degree in a relevant field (e.g., Computer Science, Mathematics). A PhD is preferred but ... Experience analyzing the behavior of frontier models in safety-critical contexts. * Experience in ...

TouchTunes

Senior Data Scientist

Montreal, QC · On-site

Use data science techniques to find data patterns, anomalies, and optimization opportunities ... Experience with Consumer Products, and/or analyzing user behavior to better drive business ...

Straumann

Sr. R&D Engineer/Scientist

Montreal, QC · On-site

Master's or PhD in Polymer Science, Materials Science, Chemical Engineering, or a related discipline. * Experience with polymer processing, melt behavior, extrusion, compounding, or thermoforming.

WSP

AI Change Enablement & Communication Lead

Montreal, QC · Hybrid

CA$135K - CA$179K/yr

With an unmatched breadth and depth of engineering, advisory and science-based expertise, our ... Collect frontline feedback, amplify success stories, reinforce safe-use behaviors, and measure ...

WSP

AI Change Enablement & Communication Lead

Montreal, QC · Hybrid

CA$135K - CA$179K/yr

With an unmatched breadth and depth of engineering, advisory and science-based expertise, our ... Collect frontline feedback, amplify success stories, reinforce safe-use behaviors, and measure ...

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All JobsBehavioural Science JobsBehavioural Science Jobs in Quebec

Behavioural Science information

See Quebec salary details

$24K

$74.2K

$128.5K

How much do behavioural science jobs pay per year?

As of Jul 16, 2026, the average yearly pay for behavioural science in Quebec is $74,235.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,000.00 and $94,000.00 per year, depending on experience, location, and employer.

What is the difference between Behavioural Science vs Data Analyst?

AspectBehavioural ScienceData Analyst
Required CredentialsDegree in Psychology, Sociology, or Behavioural ScienceDegree in Statistics, Mathematics, or Data Science
Work EnvironmentResearch settings, consulting firms, or corporate teams focusing on human behaviorData-driven environments, business intelligence, and reporting teams
Industry UsageMarketing, healthcare, policy development, and user experienceFinance, marketing, technology, and operations

While both roles analyze data, Behavioural Scientists focus on understanding human behavior and applying insights to influence decisions, whereas Data Analysts primarily interpret data to inform business strategies. The two roles often collaborate but serve different core functions within organizations.

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

To thrive as a Behavioural Scientist, you need a solid background in psychology, statistics, and research methods, usually supported by an advanced degree in behavioural science or a related field. Familiarity with statistical analysis software (such as SPSS, R, or Python), survey tools, and data visualization platforms is often required. Strong critical thinking, communication, and collaboration skills help behavioural scientists design effective studies and translate findings for diverse audiences. These abilities ensure rigorous research, actionable insights, and impactful solutions to real-world behavioural challenges.

What jobs can you do with a Behavioural Science degree?

A Behavioural Science degree prepares individuals for roles such as behavioural analyst, user experience researcher, marketing strategist, or policy advisor. These jobs often involve applying psychological principles, data analysis, and research methods to influence decision-making and improve products, services, or policies.

What is behavioural science?

Behavioural science is the study of how people make decisions and act in various situations, drawing from fields like psychology, sociology, and economics. It aims to understand human behavior by examining the factors that influence choices, habits, and social interactions. Professionals in this field use research and data to develop interventions that can change behaviors for better outcomes in areas such as health, education, and business. Behavioural scientists often work in research, policy-making, marketing, or consulting roles.

What can I do with behavioral science?

Behavioral science professionals analyze human behavior to develop strategies that influence decision-making, improve products, or enhance organizational effectiveness. They work in fields such as marketing, healthcare, finance, and public policy, often using research methods like experiments and data analysis. Skills in psychology, statistics, and data tools are essential for success in this field.

What jobs do behavioral scientists do?

Behavioral scientists analyze human behavior to develop insights that improve decision-making, product design, and policies. They work in areas such as healthcare, marketing, public policy, and user experience, often using research methods like experiments and data analysis. These roles typically require strong analytical skills and knowledge of psychology, economics, or related fields.

What can I do with a behavioral science degree?

A behavioral science degree prepares individuals for roles such as behavioral analyst, research associate, or consultant, focusing on understanding human behavior to inform decision-making and policy. Graduates often work in healthcare, marketing, public policy, or organizational development, utilizing skills in data analysis, psychology, and research methods. Certification or experience in data tools like SPSS or R can enhance job prospects.

How does a behavioural scientist typically collaborate with cross-functional teams in an organization?

Behavioural scientists frequently work alongside professionals from marketing, product development, data analytics, and human resources to integrate behavioural insights into various projects. This collaboration often involves translating research findings into actionable strategies, designing experiments or interventions, and evaluating their effectiveness through data analysis. Clear communication and the ability to explain complex concepts in accessible terms are crucial, as is adaptability to different team dynamics. These collaborations not only enhance project outcomes but also provide behavioural scientists with exposure to diverse business functions and growth opportunities.
What are popular job titles related to Behavioural Science jobs in Quebec? For Behavioural Science jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Behavioural Science jobs in Quebec look for? The top searched job categories for Behavioural Science jobs in Quebec are:
What cities in Quebec are hiring for Behavioural Science jobs? Cities in Quebec with the most Behavioural Science job openings:
Behavioural Science jobs near you
Infographic showing various Behavioural Science job openings in Quebec as of July 2026, with employment types broken down into 1% Locum Tenens, 26% Internship, 42% As Needed, 24% Full Time, 3% Part Time, and 4% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $74,235 per year, or $35.7 per hour.
Applied Research Fellow

Applied Research Fellow

The Decision Lab

Montreal, QC

Other

Re-posted 16 days ago

Job description

Description
The Decision Lab is an applied research and innovation firm. We use behavioral science & AI to help ambitious organizations create a better future. We do this by working with some of the largest organizations in the world, carrying out research in priority areas, and running one of the largest publications in applied behavioral science. In the past, we have helped organizations such as the Gates Foundation, Capital One, the World Bank, and many Fortune 500s solve some of their thorniest problems using scientific thinking.

Everything we do at TDL is guided by SPICE: Socially conscious, Pragmatic, Inventive, Catalytic, and Evidence-based. You can read more about us and our core values here.

What you'll be working on
This internship is structured as an applied research placement, designed to complement graduate-level training and provide exposure to how behavioral science & AI are used outside of purely academic settings.

Many of our current projects sit at the intersection of behavioral science and AI, including human-AI interaction, algorithmic decision-making, and responsible AI. Our past work has included partnering with Mila to behaviorally optimize an AI-powered COVID-19 contact tracing app, and building Hikai, an AI-powered CBT chatbot for workplace mental health. 

We are also actively developing Artificial Populations, a platform that uses synthetic participants to run focus groups, surveys, and interviews - getting decision-ready insights in hours rather than weeks.

Fellows interested in gaining applied AI experience will find no shortage of opportunities to do so here. Interns work on clearly scoped projects under the supervision of senior staff and contribute to ongoing research and consulting initiatives like these, with an emphasis on learning-by-doing, methodological rigor, and translating academic insights into real-world contexts.

Broadly, the role involves a mix of:
Research & Analysis (approximately 60%)
  • Conducting structured literature reviews and evidence syntheses
  • Supporting experimental design, measurement strategies, and analysis plans
  • Assisting with behavioral diagnostics and research frameworks
  • Contributing to research notes, working papers, policy briefs, or public-facing research outputs
  • Participating in internal research discussions and reviews

Applied Research Translation & Consulting Exposure (approximately 40%)
  • Supporting applied research projects with public- and private-sector partners
  • Translating research findings into practical insights and recommendations
  • Preparing client-facing deliverables (reports, deck, briefs) that translate research into actionable insights for external partners
  • Observing how academic research is adapted for policy, organizational, or technological contexts

The balance between research and applied work may vary slightly depending on project needs and the intern’s academic background.
Hear From Our Fellows
Naga Thovinakere, Applied Research Fellow
Currently involved in a project with a health tech company
"TDL's fellowship program is a great fit for anyone wanting to apply scientific rigor beyond academia. You're not just learning about behavioral science in the abstract - you're getting exposure on how it is used to inform product decisions on actual consulting engagements. If you care deeply about methodological rigor but also want your work to drive meaningful outcomes, you'll find this experience especially rewarding."

Maya Low, Applied Research Fellow
Currently involved in a project with an AI research institute
“This fellowship is a great opportunity for PhD students looking to broaden their horizons both in a research discipline outside their own and in a working environment different from academia. It's been eye-opening to watch research translate into practice and to imagine new paths for myself after my degree. On top of that, everyone at TDL is genuinely welcoming and happy to talk about their work!”
Where Fellows Have Made an Impact
 
Hilary Sweatman, Ph.D. (Neuroscience, McGill University)
Hilary worked with one of the largest nonprofit foundations to develop a framework for evaluating digital support tools in higher education. The project focused on how psychosocial factors shape student decision-making and engagement with ed-tech tools, with an emphasis on designing interventions that improve student outcomes.

Catalina Eneström, Ph.D. (Experimental Psychology, McGill University)
Catalina worked with a major global beauty company to investigate how sensory experiences drive consumer behavior, conducting a systematic literature review and contributing to a journal article on the psychology behind sustainable beauty habits.

Qualifications
Must-haves:
  • Current late stage PhD student in a relevant discipline (e.g., psychology, AI, economics, public policy, cognitive science, behavioral science, data science, or a related field)
  • Familiarity with behavioral science concepts and methods, such as experimental design, causal inference, behavioral interventions, or decision-making research
  • Strong curiosity about AI - a tinkering mindset that makes you want to try things and see how they work
  • Strong analytical and critical thinking skills, including the ability to conduct literature reviews, research syntheses, or empirical analysis to support research questions
  • Clear written communication skills in English, particularly for research summaries and analytical writing
  • Ability to work independently on scoped research tasks while engaging collaboratively with a research team
  • Ability & desire to leverage AI tools (e.g. Cursor, Claude Code, etc.) to accelerate writing, coding & analysis work
 
Preferred (but not required)
  • Exposure to applied research, policy analysis, or consulting-style work
  • Familiarity with AI-related topics (e.g., human–AI interaction, algorithmic decision-making, misinformation, or responsible AI), though technical expertise is not required
  • Interest in applied, policy-adjacent, or non-academic research career pathways
  • We recognize that students come from diverse academic traditions. Candidates are not expected to meet every criterion to be considered a strong fit.
  
We're flexible on start dates but ideally looking for a September start, and happy to work around your academic schedule and program commitments.


How to apply
To apply, please submit:
  • A short CV (1–2 pages) outlining your academic background and relevant experience
  • A brief statement of interest (up to 200 words) describing:
  • Your academic focus and current program
  • Your interest in applied behavioral science research
  • How this internship aligns with your training or career goals
 
Please note that this position is unpaid because it is meant to target PhD students who are already funded - either by their home program or through special programs at their home institution (e.g., graduate internship fellowships, doctoral internship programs, mobility awards). We do not accept candidates who want to work for free, as this unfairly prioritizes those with privileged backgrounds. To this end, please indicate your source of funding in your statement.

Shortlisted candidates will be invited to a brief conversation to discuss research interests, supervision structure, and alignment with current projects.

FAQs

Will publications or research outputs from the fellowship be affiliated with my home institution?
All research conducted during the fellowship is the intellectual property of The Decision Lab. That said, authorship is determined by contribution, so if you lead a project, you'll be credited as first author, and so on. We're happy to discuss specific publication or IP questions in more detail during the interview process.
What kinds of projects will I work on?
Projects vary throughout the year and span topics in behavioral science, public policy, healthcare, AI, education, sustainability, financial decision-making, and more. Because assignments depend on upcoming client engagements, we can't guarantee a specific project before the fellowship begins.
Will I collaborate with external organizations?
Yes. Many projects involve close collaboration with external partners, including nonprofits, government agencies, research institutes, foundations, and private-sector organizations. The level of interaction varies by project.
Are you flexible on the start date?
We typically run three (3) fellowship cohorts each year:
  • Early September – Mid December
  • Mid January – End of April
  • Early May – Mid August
We prefer fellows to start with one of these cohorts so they can engage with and learn alongside their peers throughout the program. However, we understand that individual circumstances vary, and we're happy to consider exceptions on a case-by-case basis.
What are the working hours?
The fellowship runs 16 weeks, at 37.5 hours per week, 9 AM–5 PM EST.
What does a typical week look like?
Once you're onboarded to your project, a typical week includes one or two internal team meetings alongside independent research, literature reviews, analysis, writing, and collaboration with your project team. Some projects also include regular meetings or presentations with partner organizations.
TDL IS AN EQUAL-OPPORTUNITY EMPLOYER
Research has found that women and people from marginalized backgrounds are more likely to feel that they’re unqualified for a position if they can’t check 100% of the boxes on the posting. So we’re telling you directly: you don’t need to be the perfect candidate in order to be a good fit for this role. If you’re a curious, communicative, and passionate person who loves to write about science, we want to hear from you.

More About The Decision Lab

OUR VALUES
As a social enterprise, we have a deep-rooted belief that better decisions make a better world. However, improving decisions is a messy and difficult thing. For this reason, we have laid out a clear set of criteria for what constitutes good work. Our approach is inspired by many of the organizations and individuals we use as role models.
We believe that a good approach to creating social impact is SPICE: Socially conscious, Pragmatic, Inventive, Catalytic and Evidence-based. We use these criteria to evaluate ourselves, our work, the clients we choose to take on and the people we make part of our team. Read more about SPICE below:

Socially conscious
We create positive and fair outcomes for individuals, organizations and societies.
The outcomes that societies want to achieve are constantly being discussed and revised, always a work in progress. They are not defined from the outset or from the outside. For these outcomes to be sustainable, they must integrate societal, environmental and economic dimensions.

Pragmatic
We develop solutions that are practical, effective and attainable.
We are deeply committed to bringing our ideals to life. To do so, we let the problem be the guide for our attention. We are agnostic regarding approaches and dispassionate in our assessment of candidate solutions. This unwavering focus on the problem allows us to employ the full range of tools at our disposal, deploying the right ones for each context.

Inventive
We develop solutions that are not constrained by the current reality.
When no existing solution is adequate to the problem at hand, we must move from curation to creation. Success in these contexts requires a commitment to exploration and an openness to inspiration.

Catalytic
We develop solutions that spark rapid transition to a new paradigm.
When we reach a tipping point, a small nudge sparks a change from one equilibrium state to another. By starting small and iterating quickly, we manage the change in a deliberate and responsible manner, ensuring that the catalytic reaction is positive when unleashed at scale. We can also help manage the journey to the tipping point, creating pre-conditions for catalytic projects to take off.

Evidence-based
We develop solutions that use evidence as a compass.
We are deeply committed to using evidence to guide our actions. We build evidence in-house through robust experimentation, and integrate our findings into a wider body of knowledge, coming from many people and many places. This cohesive landscape of insights allows us to triangulate the best course of action.