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Sports Analytics Machine Learning Jobs in Toronto, ON

This role will focus on translating advanced analytics, machine learning, and generative AI use cases into secure, scalable, and productionready solutions across on-prem and cloud environments ...

This role will focus on translating advanced analytics, machine learning, and generative AI use cases into secure, scalable, and productionready solutions across on-prem and cloud environments ...

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Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do sports analytics machine learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a sports analytics machine learning specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.

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

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

What job categories do people searching Sports Analytics Machine Learning jobs in Toronto, ON look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Toronto, ON are:

Infographic showing various Sports Analytics Machine Learning job openings in Toronto, ON as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 90% In-person, and 10% Hybrid job distribution.

Entry Level Machine Learning Engineer (Remote - Canada)

Yelp, Inc

Toronto, ON • Remote

Full-time

Posted 7 days ago


Yelp rating

6.9

Company rating: 6.9 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

203rd of 247 rated software companies


Job description

Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.

Yelp’s mission of connecting people with great local businesses requires the use of cutting-edge Machine Learning (ML) and Artificial Intelligence (AI) to scale across a vast and diverse base of users and businesses spanning various geographical locations. As an ML engineer, you will have the opportunity to foster these connections across millions of users and business listings using cutting-edge industry tools such as neural networks (NNs), large language models (LLMs), and traditional ML methods like XGBoost or linear models. You will be responsible for turning raw data into valuable signals and building the ML system end-to-end. This includes the full ML lifecycle from building data pipelines, training models, to deploying them in production, as well as deploying Gen AI applications.

This opportunity is fully remote and does not require you to be located in any particular area in Canada. We welcome applicants from throughout Canada. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.


  • Engage with diverse challenges such as personalizing ads, search ranking, Voice AI, AI chatbots, advertiser retention and churn prevention, data-driven storytelling, clickstream analytics, content type classification, delivering personalized recommended businesses to users, and sophisticated bot detection. 
  • Collaborate with cross functional teams, including software engineers, applied scientists, and product managers to identify and use the most relevant consumer and business data.
  • Learn the fine art of balancing scale, latency, cost, and availability depending on the problem.

  • Experience developing and productionizing machine learning models, including their supported data pipeline.
    Experience with machine learning using packages such as TensorFlow, PyTorch,
  • Spark MLlib, XGBoost, Sklearn, etc.
  • Strong coding skills in Python or equivalent (Python, Java and C++).
  • Familiarity with LLM models (Anthropic, OpenAI, Google Gemini) and Agentic design (e.g. LangGraph)
  • A passion for architecting large systems with elegant interfaces that can scale easily.
  • A hunger for tracking down root causes (no matter how deep it takes you) and fixing them in systematic ways.
  • Understanding of building data pipelines to train and deploy machine learning models and/or ETL pipelines for metrics and analytics or product feature use cases. 
  • Exposure to some of the following technologies: Apache Spark, AWS Redshift, AWS S3, Cassandra (and other NoSQL systems), AWS Athena, Apache Kafka, Apache Flink, Java, AWS and service oriented architecture.

  • There are a variety of factors that go into determining a compensation range, including but not limited to external market benchmark data and years of experience. Based on the anticipated level of experience that we are seeking, we expect the compensation range for this role to be between $[85,000] and $[107,000].  The actual compensation offered may be influenced by a variety of factors, including the candidate’s experience and skill set.

  • There may be flexibility with the range included in this posting should a candidate be leveled higher or lower than the posted range.

  • This opportunity has the option to be fully remote in all locations across Canada.
  • This role is posted to fill an existing position.
  • You can find more information about Yelp's five star benefits here!

At Yelp, we believe that diversity is an expression of all the unique characteristics that make us human: race, age, sexual orientation, gender identity, religion, disability, and education — and those are just a few. We recognize that diverse backgrounds and perspectives strengthen our teams and our product. The foundation of our diversity efforts are closely tied to our core values, which include “Playing Well With Others” and “Authenticity.”

We’re proud to be an equal opportunity employer and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, disability, or any other protected status.

We are committed to providing reasonable accommodations for individuals with disabilities in our job application process. If you need assistance or an accommodation due to a disability, you may contact us at accommodations-recruiting@yelp.com or 1-415-969-8488.

Note: Yelp does not accept agency resumes. Please do not forward resumes to any recruiting alias or employee. Yelp is not responsible for any fees related to unsolicited resumes.

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