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Applied Digital Jobs in Quebec (NOW HIRING)

Bounteous

Applied AI Engineer

Montreal, QC

Bounteous is a premier end-to-end digital transformation consultancy dedicated to partnering with ambitious brands to create digital solutions for today's complex challenges and tomorrow ...

Mcgill

Assistant Professor (CAS)

Sherbrooke, QC

Active applied research agenda in one or more fields related to multilingual digital communication and the application of AI technologies in the language and other industries * Knowledge of French ...

Mcgill

Assistant Professor (CAS)

Sherbrooke, QC · On-site

Active applied research agenda in one or more fields related to multilingual digital communication and the application of AI technologies in the language and other industries * Knowledge of French ...

Autodesk

Senior Applied AI/ML Developer

Montreal, QC · Remote

... Applied AI/ML Developer Position overview As a Senior ML Developer on the team, you will be ... for our Digital Customer Platform. * Partner with stakeholders, to solve important business ...

SYSTRA

Good understanding of ISO 19650 as applied to CDE implementation and digital project delivery * Familiarity with integration across BIM, GIS, EDMS, PMIS, and reporting environments * Knowledge of ...

trane technologies

Senior Data Scientist

Montreal, QC · On-site

Collaborate with engineering, modeling and simulation, controls, and digital teams to integrate AI ... Key Competencies Applied data science for engineering and technical domains. Generative AI and ...

New

Pfizer

Director, Medical Insights

Kirkland, QC

... Affairs, Digital & Technology, Medical Systems, and other stakeholders to enable consistent ... Understands how analytics, AI, and technology can be applied to enhance Medical and lifescience ...

New

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Applied Digital information

What does applied digital actually do?

Applied Digital is a company that provides digital infrastructure solutions, including data centers and energy management services. Employees in related roles often work with cloud technologies, cybersecurity, and operational systems to support digital operations and ensure reliable data processing. The specific responsibilities depend on the position, but generally involve technical skills and understanding of digital systems.

What are some common challenges faced by professionals in Applied Digital roles, and how can they be addressed?

Professionals in Applied Digital roles often encounter the challenge of keeping up with rapidly evolving technologies and digital tools. Staying current requires a commitment to continuous learning and professional development. Additionally, effectively collaborating with cross-functional teams—such as marketing, IT, and product management—can present communication and workflow obstacles. Building strong relationships and maintaining clear communication channels help ensure project goals are met efficiently. Adapting to changing project requirements and client expectations is also common, so flexibility and proactive problem-solving are essential for success in this field.

What skills are needed for applied digital?

Applied Digital professionals typically need strong technical skills in digital technologies such as data analysis, cybersecurity, cloud computing, and software development. Additionally, problem-solving abilities, familiarity with digital tools and platforms, and effective communication skills are important for success in this field.

What are the key skills and qualifications needed to thrive as an Applied Digital professional, and why are they important?

To thrive as an Applied Digital professional, you need a solid background in digital technologies, data analysis, and solution development, often supported by a relevant degree in computer science, information systems, or digital media. Familiarity with tools like data visualization platforms, cloud services, programming languages, and certifications in areas such as digital marketing or cloud computing is highly beneficial. Strong problem-solving, communication, and adaptability skills help you collaborate with cross-functional teams and respond effectively to evolving digital challenges. These competencies are crucial for delivering innovative digital solutions that drive business transformation and efficiency.

What's the easiest AI job to get?

Entry-level roles in applied digital or AI often include data labeling, annotation, or basic data entry positions, which require minimal technical skills and can be easier to obtain. These jobs typically involve using simple tools and may require understanding of data privacy and basic software applications, making them accessible for beginners entering the AI field.

What is the difference between Applied Digital vs Digital Marketing Specialist?

AspectApplied DigitalDigital Marketing Specialist
Required CredentialsRelevant degrees, certifications in digital toolsMarketing degrees, certifications in SEO, SEM
Work EnvironmentDigital agencies, tech companies, marketing teamsMarketing firms, corporate marketing departments
Industry UsageUsed across tech, marketing, advertising sectorsPrimarily in marketing and advertising sectors

Applied Digital roles focus on digital technology implementation and digital project management, often requiring technical certifications. Digital Marketing Specialists concentrate on marketing strategies, content creation, and campaign management. While both roles operate in digital environments, Applied Digital is more technical, whereas Digital Marketing Specialists focus on marketing tactics and customer engagement.

What are applied digital jobs?

Applied digital jobs involve using digital technologies and data-driven solutions to solve real-world business problems. Professionals in this field work with tools like data analytics, software applications, and digital platforms to improve processes, enhance customer experiences, and support decision-making. Roles can range from digital project managers to data analysts, UX designers, and digital marketers. These jobs are found across industries as organizations increasingly rely on digital transformation to stay competitive.

Is Applied Digital a good company to work for?

Applied Digital is a company that provides digital infrastructure solutions, and employment experiences can vary based on roles and departments. Employees generally report a professional environment, but reviews about work-life balance and management differ across sources. It is advisable to research specific roles and read employee reviews for a comprehensive understanding.
What are popular job titles related to Applied Digital jobs in Quebec? For Applied Digital jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Applied Digital jobs in Quebec look for? The top searched job categories for Applied Digital jobs in Quebec are:
Applied Digital jobs near you
Infographic showing various Applied Digital job openings in Quebec as of July 2026, with employment types broken down into 77% Full Time, 22% Part Time, and 1% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.
Applied Research Fellow

Applied Research Fellow

The Decision Lab

Montreal, QC

Other

Posted 24 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.