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Remote Machine Learning Jobs in Toronto, ON (NOW HIRING)

Data Scientist

Toronto, ON ยท Remote

CA$70K - CA$80K/yr

This position is remote but may require to be in-office in Toronto for team collaborations ... Apply foundational AI and machine learning techniques to support projects such as recommendation ...

Experience building and training statistical and machine learning models (classifiers, regression models...) Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC ...

ML/AI Engineer

Toronto, ON ยท On-site +1

CA$110K - CA$150K/yr

The ML / AI Engineer design, build, deploy, and operate production-grade machine learning and ... The role will be remote. Why Join Levio? * Work on complex,high impactdigital transformation ...

Follow advancements in data science, machine learning, and healthcare analytics Qualifications ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

Develop and maintain novel microbiome metrics and biomarkers using statistical and machine learning ... Remote-first, real overlap Our FTEs are based in North America and work core hours from 9am-6pm CST ...

Data Scientist Manager

Maple, ON ยท On-site +1

CA$125K - CA$180K/yr

Lead the design, development, deployment, and scaling of enterprise AI, Machine Learning, Generative AI, and Agentic AI solutions aligned with Sanofi's Digital Global Business Unit strategic ...

Showing results 41-60

Remote Machine Learning information

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Machine Learning jobs in Toronto, ON?

The most popular types of Machine Learning jobs in Toronto, ON are:

What are popular job titles related to Remote Machine Learning jobs in Toronto, ON?

For Remote Machine Learning jobs in Toronto, ON, the most frequently searched job titles are:

Infographic showing various Remote Machine Learning job openings in Toronto, ON as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution.

Data Scientist

Toronto, ON โ€ข Remote

CA$70K - CA$80K/yr

Full-time

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

At CanadaHelps we believe in the power of generosity - not just for those who receive it, but for everyone it touches. Every act of generosity sparks connection, inspires change, and brings people together. This is an opportunity to join something bigger: a movement that fuels progress, strengthens communities, and reminds us of what's possible when we come together.


We are a dedicated team of entrepreneurial-minded peers who believe in a world where everyone can thrive. We offer a flexible, inclusive environment built on growth, ambition, and shared success.


CanadaHelps provides the most comprehensive and flexible range of giving solutions for donating to any charity in Canada, and we partner with charities of all sizes to ensure they have the tools they need to achieve their goals.

About the role:

We are looking for a full-time Data Scientist. The ideal candidate will be a strong partner to cross-functional teams, in understanding new and existing product offerings, and recommend advanced analytical products and solutions. We are looking for someone who loves to solve problems using various advanced analytical techniques and algorithms.

Reporting to the Director of Data & Analytics, your primary focus is advanced analytics - building models, uncovering behavioural and usage patterns, and generating insights that help charity partners and donors make smarter, data-driven decisions. This is an ideal opportunity for someone that wants to "use data science for good" and apply statistical and machine learning techniques to solve real-world social impact challenges. This is a new role.


The annual salary range for this role is $70,000 - $80,000. Where an offer falls within this range is determined through the interview process. Candidates are benchmarked by the hiring team based on role scope, relevant experience, skill alignment, and expected impact, using consistent and objective criteria.


This position is remote but may require to be in-office in Toronto for team collaborations.


Responsibilities:

Responsibilities will include but are not limited:

  • Charity Data Expertise:Become a subject matter expert on how charity data is stored and structured across multiple systems.
  • Conduct advanced analyses on donor behaviour, fundraising trends, and platform engagement
  • Support the development, testing, and deployment of predictive models (e.g., donor segmentation, churn prediction, lifetime value estimation)
  • Explore large datasets to identify patterns, anomalies, and opportunities for optimization
  • Collaborate with product, engineering, and marketing teams to evaluate experiments and measure the impact of new features or campaigns
  • Build clear, accessible dashboards and visualizations that complement deeper analytical work
  • Contribute to research projects that examine trends in Canadian giving and the charitable sector
  • Communicate findings through compelling narratives tailored to both technical and nontechnical audiences
  • Help maintain data quality, documentation, and analytical best practices
  • Apply foundational AI and machine learning techniques to support projects such as recommendation systems, classification models, and automated insight generation


Required Skills and Experience:

  • A degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related field
  • Strong skills in Python or R, plus experience with SQL
  • 1-2 years of hands-on experience in statistical modelling, machine learning, and experimental design
  • Interest or emerging experience in AI/ML techniques, such as working with classification models, clustering, natural language processing, or recommendation systems
  • Comfort learning new tools, frameworks, and AIdriven approaches as the field evolves
  • Ability to translate complex analytical results into actionable insights
  • 1-2 years of applied experience with data visualization tools (Tableau, Power BI, or similar)
  • A collaborative mindset and enthusiasm for contributing to a mission-driven organization
  • A natural sense of data curiosity - you enjoy exploring datasets, asking thoughtful questions, and digging deeper to uncover what's really happening beneath the surface
  • Strong storytelling skills, with the ability to craft clear, compelling narratives that help stakeholders understand the "so what" behind the data
  • Exceptional communication skills, both verbal and written.
  • Knowledge of using CRM tools such as Salesforce and web analytics tools, and experience in experimentation (A/B testing, experimental design) an asset
  • Experience in and ability to play "trusted advisor" to internal stakeholders and help make change happen.
  • Fast learner. Being a fast learner also means the ability to admit defeat, ask for help and iterate quickly so you can learn from your mistakes and move ahead.


We believe in everyone

At CanadaHelps, we commit to pursuing deliberate efforts to ensure that our company is a place where differences are welcomed, different perspectives are respectfully heard and where every individual feels a sense of belonging and inclusion. We know that by creating a vibrant climate of inclusiveness, we can more effectively advance our collective capabilities.


AI in Recruitment :

CanadaHelps does not use AI-enabled tools to screen, assess, rank, or select candidates in our recruitment process. Our hiring teams make all hiring decisions.