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Entry Level Data Scientist Machine Learning Jobs in Toronto, ON

The Role We're hiring a Senior Data Scientist to own machine-learning models end to end - from framing the problem and designing the model through the training pipeline, deployment to a live endpoint ...

Data Scientist - TD Asset Management

Toronto, ON ยท On-site

CA$105K - CA$145K/yr

Help to grow a team of data scientists and software engineers * Partner closely with portfolio ... Strong background in machine learning, large language models (LLMs), agentic AI frameworks, and ...

As a Data Scientist, you will contribute meaningfully through leading others. WHO WE ARE LOOKING ... machine learning * You think beyond just the task at hand to deeply understand the 'why' behind ...

Senior Machine Learning Engineer

Toronto, ON ยท Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... data scientists, and pathology domain experts to integrate research into production systems ...

Senior Machine Learning Engineer

Toronto, ON ยท Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... data scientists, and pathology domain experts to integrate research into production systems ...

Showing results 41-60

Entry Level Data Scientist Machine Learning information

What is an entry level data scientist machine learning?

Entry level data scientist machine learning jobs are positions for individuals who are new to the field of data science and machine learning. These roles typically focus on working with data, building and testing machine learning models, and supporting more experienced data scientists. Entry level professionals may clean and analyze data, implement basic algorithms, and help interpret results to inform business decisions. These jobs often require proficiency in programming languages like Python or R, foundational knowledge of statistics, and some experience with machine learning libraries.

What are the key skills and qualifications needed to thrive as an entry level data scientist machine learning?

To thrive as an Entry Level Data Scientist in Machine Learning, you need a solid background in statistics, programming (Python or R), and foundational machine learning concepts, typically supported by a relevant degree in computer science, data science, or a related field. Familiarity with tools and libraries such as scikit-learn, TensorFlow, Pandas, and SQL, as well as experience with data visualization platforms, is highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly set candidates apart. These skills are essential for effectively analyzing data, building predictive models, and translating complex results into actionable business insights.

What are some common challenges faced by entry level data scientists working with machine learning models?

Entry-level data scientists often encounter challenges such as cleaning and preparing messy or incomplete datasets, selecting appropriate algorithms for specific problems, and tuning model parameters to achieve optimal performance. In addition, they may need to clearly communicate technical findings to non-technical stakeholders and collaborate closely with team members from engineering, product, and business departments. Gaining experience in version control, reproducibility, and model deployment are also important steps in mastering the end-to-end machine learning workflow.

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

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

What are popular job titles related to Entry Level Data Scientist Machine Learning jobs in Toronto, ON?

For Entry Level Data Scientist Machine Learning jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Scientist Machine Learning jobs in Toronto, ON look for?

The top searched job categories for Entry Level Data Scientist Machine Learning jobs in Toronto, ON are:

Infographic showing various Entry Level Data Scientist Machine Learning job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution.

AI Scientist, Advanced Analytics and AI (8 Month Contract)

CIBC US

Toronto, ON โ€ข Hybrid

Full-time

Posted 13 days ago


Job description

We're building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what's right for our clients.

At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.

To learn more about CIBC, please visit CIBC.com

What you'll be doing

The Fraud, Cyber, and Client Account Management Artificial Intelligence team helps protect our clients and the bank by building intelligent solutions that support faster, more informed decision-making. As an AI Scientist, Advanced Analytics and AI, you'll develop, test, deploy, and monitor artificial intelligence and machine learning solutions that address complex business challenges. You'll work with data to uncover insights, support model development, and help translate business needs into scalable analytical solutions. You'll build and enhance traditional machine learning models using libraries such as scikit-learn and XGBoost to solve fraud analytics use cases. You'll collaborate with partners across technology and business teams to deliver models that are practical, reliable, and aligned to client and operational needs. In this role, you'll also contribute to improving model performance, supporting implementation, and monitoring outcomes to help ensure solutions continue to deliver value over time.

At CIBC we enable the work environment most optimal for you to thrive in your role. You'll have the flexibility to manage your work activities within a hybrid work arrangement where you'll spend 1-3 days per week on-site, while other days will be remote.

How you'll succeed

  • Model Development - Develop and test artificial intelligence and machine learning models to support fraud, cyber, and client account management use cases.
  • Data Analysis - Use tools such as Python, PySpark, SQL, and Databricks to prepare data, perform analysis, and generate insights that inform model design and performance.
  • Deployment Support - Contribute to deploying analytical solutions into production environments and support implementation activities with partners across technology and business teams. Participate in the end-to-end machine learning lifecycle, including data preparation, model development, validation, deployment, monitoring, and continuous improvements in partnership with engineering teams.
  • Model Monitoring - Monitor model performance, identify issues or opportunities for improvement, and help maintain reliable, scalable solutions over time.
  • Collaboration - Work closely with cross-functional teams to understand business needs, communicate findings clearly, and support the delivery of practical, high-impact solutions.

Who you are

  • You have 2-4 years of experience in. data science, machine learning, advanced analytics, or a related field. You have hands-on experience working with Python, PySpark, SQL, and Databricks in a production analytics environment.
  • You have a degree in. Computer Science, Mathematics, Statistics, Business, or a related discipline.
  • You give meaning to data. You enjoy working with data to solve problems, identify patterns, and turn complex information into meaningful insights.
  • You're motivated by collective success. You work well with others and can explain technical concepts in a clear, thoughtful way to different audiences.
  • You look beyond the moment. You're focused on continuous improvement. You look for ways to enhance model performance, strengthen processes, and support better outcomes for clients and the business.
  • Values matter to you. You bring your real self to work, and you live our values - trust, teamwork, and accountability.

What CIBC Offers

At CIBC, your goals are a priority. We start with your strengths and ambitions as an employee and strive to create opportunities to tap into your potential.

  • We work to recognize you in meaningful, personalized ways including a competitive compensation, a banking benefit*, wellbeing support and additional offers such as employee and family assistance programs and MomentMakers, our social, points-based recognition program.

  • Our spaces and technological toolkit will make it simple to bring together great minds to create innovative solutions that make a difference for our clients.

*Subject to program terms and conditions

What you need to know

  • CIBC is committed to creating an inclusive environment where all team members and clients feel like they belong. We seek applicants with a wide range of abilities and we provide an accessible candidate experience. If you need accommodation, please contact Mailbox.careers-carrieres@cibc.com

  • CIBC is committed to clarity in our hiring process. All roles posted are opportunities we're actively recruiting for, unless stated otherwise.

  • You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit

  • We may ask you to complete an attribute-based assessment and other skills test (such as simulation, coding, French proficiency).

  • We use artificial intelligence tools during the recruitment process. Our goal for the application process is to get to know more about you, all that you have to offer, and give you the opportunity to learn more about us.

Expected End Date

2027-04-30

Job Location

Toronto-81 Bay, 21st Floor

Employment Type

Temporary (Fixed Term)

Weekly Hours

37.5

Skills

Advanced Analytics, Analytical Thinking, Artificial Intelligence (AI), Data Analysis, Data Analytics, Data Science, Machine Learning (ML), Model Development, Natural Language, Natural Language Processing (NLP), Predictive Analytics, Problem Solving, Python (Programming Language), Statistics, Structured Query Language (SQL), Teamwork