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Data Science Intern jobs in Toronto, ON

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    • 3+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology,…
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    • 3+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology,…
    • 3+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology,…
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    • 3+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology,…
    • Perform data queries and prepare data sets for analysis /modelling , including cleaning data and feature engineering.
    • 5+ years of experience in data science, machine learning engineering, applied ML, or a related production-focused role.
    • Perform SQL data queries and support data sets for analysis/modelling, including cleaning data and feature engineering.
    • Understand business context and data infrastructure and translate business problems to viable data science solutions.
    • Scope of role may have enterprise impact.
    • 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.
    • Proficiency in Excel and data analysis tools.
    • Develop dashboards, reports, and data visualizations to support decision-making.
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    • Support new credit strategy development with advanced analytics and data science.
    • 2+ years of experience performing advanced analytics or data science, ideally…
    • Bachelor’s degree in computer science, engineering, data science, mathematics or a related discipline.
    • 5 plus years of progressive software engineering, machine…
    • 5+ years across data science & ML, including retail/operations use-cases (or adjacent large-scale domains).
    • We’re looking for an Applied ML Lead Scientist who…
    • During my time as an intern at CaptiveAire, I was able to grow my communication and technical skills and gain practical experience that complemented my time as…
    • Coach junior data scientists on AI engineering, ML integration best practices, and effective data science project delivery.
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Data Science Consultant - AI Trainer
North York, ON
Remote
$50.00–$140.56 an hour
Fixed term contract, Contract

Job details

Here’s how the job details align with your profile.

Pay

$50.00–$140.56 an hour

Job type

Fixed term contract
Contract

Benefits

Pulled from the full job description
Flexible schedule

Full job description

DataAnnotation is committed to creating quality AI. Help train AI chatbots while gaining the flexibility of remote work and choosing your own schedule.

We are looking for an existing Data Science Consultant - AI Trainer to help train AI models. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice. That's where you come in.

You'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here. You can fit this work alongside a full-time role, or treat it as your primary focus, choosing projects and schedules that align with your availability and goals.

To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Advantages of contracting with us:

  • Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand.
  • Flexible schedule: choose which projects you take on and when you work, on your own computer, from the comfort of your own home.
  • Competitive pay: projects are paid hourly at $50 to $100 USD per hour, with bonus rates available on some projects.
  • Impact: help shape the future of AI systems built to reason about data and analytics.

Responsibilities:

  • Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity.
  • Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.
  • Write clear technical explanations and well-documented analytical code.
  • Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning.

Qualifications:

  • 3+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.
  • Some coding experience required, with comfort writing and reviewing analytical code end-to-end.
  • Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting).
  • Fluency in English (native or bilingual level) with strong writing skills.
  • A bachelor's degree in a quantitative field preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); an advanced degree (Master’s or PhD) is a plus.
  • Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise).

Note: Payment is made via PayPal. We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand.

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