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Science Jobs in Ontario (NOW HIRING)

Oxford Learning Centres, Inc.

$19/hr

Sharp with science? Excited by equations in both fields? Eager to help students succeed in math and science? Our hours count! Gain valuable teaching experience! Oxford Learning St. Catharines is ...

Amplity Health

Regional Medical Science Liaison (MSL) Oncology (Breast Cancer) Location: Poland or Czech Republic Territory: Poland & Czech Republic & DACH Client: US-Based Biopharmaceutical Company | Precision ...

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All JobsScience JobsScience Jobs in Ontario

Science information

See Ontario salary details

$21.5K

$74.5K

$175.5K

How much do science jobs pay per year?

As of Aug 16, 2026, the average yearly pay for science in Ontario is $74,494.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,500.00 and $100,000.00 per year, depending on experience, location, and employer.

What is the difference between Science vs Laboratory Technician?

AspectScienceLaboratory Technician
Required CredentialsBachelor's degree in science or related fieldAssociate's degree or certification in laboratory technology
Work EnvironmentResearch labs, universities, industry research centersClinical, industrial, or research laboratories
Employer & Industry UsageAcademic, research institutions, private companiesHospitals, diagnostic labs, manufacturing plants
Common Search & ComparisonFocuses on research, analysis, and scientific discoveryFocuses on conducting tests, preparing samples, and supporting research

Science professionals typically engage in research, experimentation, and analysis within labs or academic settings, often requiring advanced degrees. Laboratory Technicians support these efforts by performing tests, preparing samples, and maintaining lab equipment, usually with technical certifications. Both roles are essential in scientific and industrial environments, but their responsibilities and educational requirements differ significantly.

What are some careers in science?

Careers in science include roles such as research scientist, laboratory technician, environmental scientist, biologist, chemist, physicist, and data analyst. These positions often require strong analytical skills, knowledge of scientific methods, and proficiency with specialized tools or laboratory equipment.

What are science jobs?

Science jobs encompass a wide range of careers that involve researching, analyzing, and applying scientific principles to solve problems and advance knowledge. These roles can be found in various fields such as biology, chemistry, physics, environmental science, and more. Science professionals may work in laboratories, research institutions, academia, industry, or government agencies, often focusing on experimentation, data analysis, and innovation. Their work contributes to technological advancements, public health, environmental protection, and education.

What are some common challenges faced by professionals working in scientific research roles?

Professionals in scientific research often encounter challenges such as securing funding for projects, managing tight deadlines for experiments, and adapting to rapidly evolving technologies. Collaboration across multidisciplinary teams is frequent, requiring clear communication and strong project management skills. Additionally, interpreting complex data and publishing results in reputable journals can be demanding but are essential for career progression in the field.

What science careers are in demand?

As technology continues to advance, the demand for science professionals continues to increase. One of the science careers in highest demand is a research technician. A research technician’s duties are to set up, operate, and maintain lab equipment. Another in-demand job is that of a senior researcher. A senior researcher’s responsibilities are to work in a lab and conduct experiments. Other science jobs with significant demand include that of clinical project manager, chief scientific officer, and biotechnology specialist. Chemists, engineers, physicists, geologists, and technical writers are all science jobs currently in high demand.

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

To thrive as a Scientist, you need a strong background in scientific methodology, data analysis, and subject-specific knowledge, typically supported by at least a bachelor's or master's degree in a science field. Familiarity with laboratory equipment, statistical software, and data management systems is often required, along with relevant certifications depending on specialization. Critical thinking, problem-solving, and effective communication are essential soft skills for designing experiments and sharing findings. These skills ensure accurate research, meaningful discoveries, and clear dissemination of scientific knowledge.
More about Science jobs

What are the most commonly searched types of Science jobs in Ontario?

The most popular types of Science jobs in Ontario are:

What are popular job titles related to Science jobs in Ontario?

For Science jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Science jobs in Ontario look for?

The top searched job categories for Science jobs in Ontario are:

What cities in Ontario are hiring for Science jobs?

Cities in Ontario with the most Science job openings:

Science jobs near you
Infographic showing various Science job openings in Ontario as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 68% Full Time, 27% Part Time, and 3% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $74,494 per year, or $35.8 per hour.

Full Stack Data Science Engineering Specialist

Td

Toronto, ON • On-site

CA$187K - CA$261K/yr

Full-time

Re-posted 15 days ago

Job description

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$187,500 - $261,000 CADThe pay details posted reflect a temporary market premium specific to this role that is reassessed annually.

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Department Overview

Join a high-impact analytics team that shapes business decisions through data, insights, and AI/ML. Collaborate with business leaders and cross-functional teams to uncover opportunities, build scalable analytics solutions, and translate complex analysis into actionable insights.

Key Responsibilities

  • Lead end-to-end performance diagnostics across customer, product, and advisor dimensions to identify growth, efficiency, and primacy opportunities.
  • Translate curated data into actionable insights through hypothesis development, testing, analysis, and stakeholder storytelling.
  • Design and deliver scalable analytics assets, including datasets, dashboards, segmentation frameworks, and predictive AI/ML models.
  • Investigate, evaluate, and implement AI/ML tools and algorithms to solve complex business problems.
  • Develop compelling visualizations and data stories tailored to technical and non-technical audiences.
  • Partner with business owners to drive advanced analytics and AI/ML adoption.
  • Lead cross-functional collaboration with data scientists, engineers, IT partners, and business process owners.
  • Provide subject-matter expertise, mentorship, and guidance on advanced analytics and AI/ML methodologies.
  • Identify emerging analytical trends and data needs to improve repeatable and scalable solutions.

Required Qualifications & Skills

  • Business Acumen: Strong ability to frame and structure complex business problems in financial services / retail banking, connect analytical insights to commercial levers (growth, efficiency, customer and advisor outcomes), and translate findings into clear, actionable recommendations. Demonstrated comfort engaging with senior executives and Csuite stakeholders, influencing decisions through concise, insightdriven storytelling.
  • Applied Analytics Expertise: Demonstrated ability to creatively explore data, identify nonobvious patterns, and rigorously test hypotheses to solve complex business problems. Brings an entrepreneurial mindset to analytics by proactively identifying opportunities, challenging assumptions, and delivering highimpact insights that drive informed decisionmaking.
  • ML/AI Lifecycle Familiarity: Experience working with existing ML/AI models (adjusting inputs, interpreting outputs) and building or modifying models as needed. Solid knowledge of applied Machine Learning, Deep Learning, Large Language Models
  • Solid cloud experience with Azure or AWS and cloud AI/ML services such as Databricks, Kubernetes, docker and container orchestration, Azure Machine Learning, Azure Data Factory
  • Visualization & Communication: Proficient in creating clear, compelling dashboards, visualizations, and data stories tailored to diverse audiences, including senior executives and Csuite leaders, translating complex analysis into concise, decisionready narratives.
  • Data Stewardship: Confident working with structured and unstructured data from multiple sources, ensuring data usability, cleanliness, and reliability. Able to build or modify data pipelines or analytical assets.
  • Core Analytical Tools: Proficient in Python, PySpark, SQL, Power BI, and Databricks (or similar platforms) for data preparation, analysis, and collaboration.
  • Strong experience with PySpark for big data processing and PyTorch for deep learning model serving.
  • Non-Technical Skills: Strong relationship management, storytelling, and business communication skills for senior audiences.

Education & Experience

  • A graduate or undergraduate degree in a quantitative or analytics-focused discipline (e.g., Business Analytics, Data Science, Statistics, Mathematics, Engineering, Computer Science, Finance, Actuarial Science).
  • 10 years of relevant experience in advanced analytics, data science, or applied AI/ML in domains such as financial services, technology, consulting, or similar industries
  • Data Manipulation: SQL, PySpark, Python
  • AI & ML: Predictive Analytics, Natural Language Processing (NLP), Supervised and Unsupervised Learning, leveraging Generative AI tools and APIs, Model Development and Deployment, Experimentation and Optimization including emerging capabilities and their application in analytical workflows.
  • Data Visualization: Power BI, Tableau
  • Cloud & Big Data Platforms: Azure (ADF, Synapse, Databricks), Snowflake
  • Data Engineering: ETL/ELT Pipelines, Apache Spark

Nice-to-Have

  • Experience in customer analytics within financial services (e.g., engagement, onboarding, cross-sell, retention, productivity insights).
  • Expertise in optimizing analytical assets (data pipelines, models, dashboards) to drive measurable business impact.
  • Bilingual proficiency (English/French).
Apercu du departement

Joignez-vous a une equipe d'analytique strategique qui soutient la prise de decision d'affaires grace a des analyses rigoureuses, aux donnees et aux capacites d'intelligence artificielle et d'apprentissage automatique (IA/AA). En partenariat etroit avec les leaders d'affaires et les equipes transversales, vous contribuerez a identifier des occasions a forte valeur ajoutee, a developper des solutions analytiques durables et a transformer des analyses complexes en recommandations claires, concretes et responsables.

Responsabilites principales
  • Diriger des analyses de performance de bout en bout couvrant les dimensions clients, produits et conseillers, afin d'identifier des occasions d'amelioration liees a la croissance, a l'efficacite operationnelle et a la relation client.
  • Convertir les donnees en informations exploitables par l'elaboration d'hypotheses, leur validation analytique et la communication structuree des constats aux parties prenantes.
  • Concevoir, developper et maintenir des actifs analytiques evolutifs, incluant des ensembles de donnees, des tableaux de bord, des cadres de segmentation et des modeles predictifs en IA/AA.
  • Evaluer et mettre en uvre des outils, techniques et algorithmes d'IA/AA afin de repondre a des enjeux d'affaires complexes, dans le respect des cadres de gouvernance et de gestion des risques.
  • Produire des visualisations et des recits de donnees clairs et percutants, adaptes a des publics techniques et non techniques.
  • Travailler en etroite collaboration avec les partenaires d'affaires afin de favoriser l'adoption de l'analytique avancee et de l'IA/AA a l'echelle de l'organisation.
  • Assurer une collaboration efficace avec les equipes de science des donnees, d'ingenierie, des TI et les responsables des processus d'affaires.
  • Agir comme expert-conseil, en offrant du mentorat et de l'accompagnement sur les methodologies avancees en analytique et en IA/AA.
  • Surveiller les tendances emergentes en analytique et les besoins en donnees afin d'ameliorer la reutilisabilite, la robustesse et l'evolutivite des solutions.
Qualifications et competences requises

Sens des affaires et communication executive

  • Capacite demontree a structurer et a resoudre des problematiques complexes dans les services financiers et les services bancaires de detail.
  • Aptitude a relier les resultats analytiques aux leviers d'affaires (croissance, efficacite, experience client et performance des conseillers) et a formuler des recommandations claires et orientees vers l'action.
  • Aisance a interagir avec des cadres superieurs et la haute direction, en influencant les decisions grace a une communication concise, factuelle et axee sur les insights.

Expertise en analytique appliquee

  • Solide experience en exploration de donnees, en identification de tendances non evidentes et en validation rigoureuse d'hypotheses afin de soutenir des decisions d'affaires eclairees.
  • Approche proactive et structuree, axee sur l'amelioration continue et la creation de valeur mesurable.

IA et apprentissage automatique

  • Experience avec des modeles existants d'IA/AA (ajustement des parametres, interpretation des resultats) ainsi qu'avec la conception ou l'evolution de modeles, au besoin.
  • Bonne connaissance de l'apprentissage automatique applique, de l'apprentissage profond et des grands modeles de langage (LLM).

Infonuagique et plateformes analytiques

  • Experience avec des environnements infonuagiques tels qu'Azure ou AWS et avec des services d'IA/AA incluant Databricks, Kubernetes, Docker, Azure Machine Learning et Azure Data Factory.

Visualisation et narration des donnees

  • Capacite a concevoir des tableaux de bord et des visualisations clairs, coherents et adaptes a divers niveaux de public, incluant la haute direction, en mettant l'accent sur la prise de decision.

Gestion et qualite des donnees

  • Aisance a travailler avec des donnees structurees et non structurees provenant de sources multiples, en assurant leur qualite, leur fiabilite et leur conformite aux normes internes.
  • Capacite a concevoir ou a ameliorer des pipelines de donnees et des actifs analytiques.

Outils analytiques

  • Maitrise de Python, PySpark, SQL, Power BI et Databricks (ou outils comparables).
  • Experience confirmee avec PySpark pour le traitement de donnees volumineuses et PyTorch pour le deploiement de modeles d'apprentissage profond.

Competences interpersonnelles

  • Excellentes habiletes en collaboration, en gestion des relations et en communication d'affaires aupres de partenaires et de dirigeants.
Formation et experience
  • Diplome universitaire (baccalaureat ou maitrise) dans un domaine quantitatif ou analytique (analytique d'affaires, science des donnees, statistique, mathematiques, genie, informatique, finance, actuariat).
  • 10 annees d'experience pertinente en analytique avancee, science des donnees ou IA/AA appliquee, idealement dans les services financiers, la technologie ou le conseil.

Competences techniques cles

  • Manipulation des donnees : SQL, PySpark, Python
  • IA et AA : analytique predictive, traitement du langage naturel (NLP), apprentissage supervise et non supervise, IA generative, developpement et deploiement de modeles, experimentation et optimisation
  • Visualisation : Power BI, Tableau
  • Infonuagique et donnees massives : Azure (ADF, Synapse, Databricks), Snowflake
  • Ingenierie des donnees : pipelines ETL/ELT, Apache Spark
Atouts
  • Experience en analytique client dans un contexte de services financiers (engagement, integration, ventes croisees, retention, productivite).
  • Capacite demontree a optimiser des actifs analytiques afin de generer des resultats d'affaires mesurables.
  • Bilinguisme (francais et anglais).

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/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We're delighted that you're considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. You'll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you're passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair op...

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