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Remote Data Science Intern Jobs in Ontario (NOW HIRING)

Apply advanced data science and machine learning techniques across a wide range of use cases including predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP ...

Apply advanced data science and machine learning techniques across a wide range of use cases including predictive modeling, forecasting, classification, anomaly detection, recommendation systems, NLP ...

AI Research Scientist - PhD

Toronto, ON ยท Remote

CA$55 - CA$80/hr

Remote Role Responsibilities * Contribute subject matter expertise to a cutting-edge project ... PhD or advanced degree in Medicine / Healthcare , Statistics and Data Science , AI / ML Research ...

Showing results 21-40

Remote Data Science Intern information

What is a remote data science intern?

A Remote Data Science Intern is a student or recent graduate who works with a company or organization on data science projects while working from a location outside the main office, typically from home. Their tasks often include analyzing large datasets, creating data visualizations, building statistical models, and supporting the team with data-driven insights. Remote internships offer flexibility and allow interns to gain real-world experience in data science while collaborating with teams using digital communication and project management tools. This type of internship helps interns build valuable technical and soft skills that are essential in the evolving data science field.

What types of projects does a remote data science intern typically work on, and how do they collaborate with their team?

Remote Data Science Interns often work on projects such as data cleaning, exploratory data analysis, building predictive models, or developing data visualizations. Collaboration typically occurs through virtual meetings, shared code repositories, and project management tools, allowing interns to interact regularly with data scientists, engineers, and business analysts. Interns are usually assigned a mentor or supervisor who provides guidance and feedback, helping them align their work with team objectives. This setup not only enhances technical growth but also fosters communication and teamwork skills essential for future roles.

What is the difference between Remote Data Science Intern vs Remote Data Analyst?

AspectRemote Data Science InternRemote Data Analyst
Required CredentialsTypically pursuing or recently completed a degree in Data Science, Computer Science, or related fieldsOften holds a degree in Statistics, Mathematics, or related areas; may have certifications in data analysis tools
Work EnvironmentInternship programs, often part-time or project-based, with mentorshipFull-time or part-time remote roles, focusing on data interpretation and reporting
Employer & Industry UsageUsed by tech companies, startups, and research institutions for entry-level talentCommon across finance, marketing, healthcare, and tech industries for data-driven decision making

The main difference between a Remote Data Science Intern and a Remote Data Analyst lies in experience and scope. Interns are typically students or recent graduates gaining hands-on experience, while Data Analysts are more experienced professionals focused on analyzing and interpreting data to support business decisions. Both roles often work remotely and require familiarity with data tools, but their responsibilities and career stages differ.

What are the key skills and qualifications needed to thrive as a remote data science intern, and why are they important?

To thrive as a Remote Data Science Intern, you need a solid background in statistics, programming (Python or R), and data analysis, typically supported by coursework in data science or related fields. Familiarity with tools like Jupyter Notebook, SQL databases, and version control systems such as Git is often expected. Strong problem-solving abilities, self-motivation, and clear communication skills help you collaborate effectively and manage tasks independently in a remote setting. These skills ensure you can analyze data accurately, contribute to team projects, and adapt to the demands of remote work environments.
What are the most commonly searched types of Remote Data Science jobs in Ontario? The most popular types of Remote Data Science jobs in Ontario are:
What are popular job titles related to Remote Data Science Intern jobs in Ontario? For Remote Data Science Intern jobs in Ontario, the most frequently searched job titles are:
What cities in Ontario are hiring for Remote Data Science Intern jobs? Cities in Ontario with the most Remote Data Science Intern job openings:
Infographic showing various Remote Data Science Intern job openings in Ontario as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 12% Part Time, and 7% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Applied Machine Learning Scientist

StackAdapt

London, ON โ€ข On-site, Remote

Other

Re-posted 4 days ago


Job description

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers and advertisers worldwide and as a result, we're dealing with millions of requests each second, making billions of decisions. We utilize the latest technologies to solve challenges in traffic, data storage, machine learning, and scalability.
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Want to learn more about our Data Science Team: https://alldus.com/ie/blog/podcasts/aiinaction-ned-dimitrov-stackadapt/
Learn more about our team culture here: https://www.stackadapt.com/careers/data-scienceย 
Watch our talk at Amazon Tech Talks: https://www.youtube.com/watch?v=lRqu-a4gPuU
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StackAdapt is a Remote First company, and we are open to candidates located anywhere in the UK, Ireland and Germany for this position.
What you'll be doing:
  • Innovate ML algorithms to maximize ROI and advertising performance. This ranges from creating entirely new algorithms, to improvements on state-of-the art methods, to development using a deep understanding of classic methods
  • Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms
  • Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights
What you'll bring to the table:
  • Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
  • Have the ability to take an ambiguously defined task, and break it down into actionable steps
  • Have a comprehensive understanding of statistics, optimization and machine learning
  • Are proficient in coding, data structures, and algorithms
  • Enjoy working in a friendly, collaborative environment with others