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Algorithm Research Jobs in Toronto, ON (NOW HIRING)

This role offers a unique opportunity to shape next-generation home security technology while advancing the field of AI algorithms and systems. The team is focused on productizing research in ...

Lead R&D of industry-leading algorithms for LLM finetuning paradigms, Autonomous Agents, Knowledge Graph, Generative AI, Responsible AI and their applications in financial domains to significantly ...

The Science team on Ads & Offers designs and builds the core algorithmic components of this system ... S. in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields ...

... algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative ...

... algorithm performance, validate research hypotheses, and drive iterative improvements Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative ...

... AI algorithms and systems. The team is focused on productizing research in computer vision and GenAI into products that benefit millions of customers worldwide, such as real-time object detection ...

Become a member of ourworld-class software research and development team!Altera develops ... Designing, developing, and improving placement algorithms for our FPGA CAD software tools

... and algorithmic solutions. Build analytical solutions for complex P&C claims operations ... Research, recommend, and implement AI methodologies appropriate for the given risk assessment ...

Develop and enhance algorithms for efficient data movement, local data processing, job submission ... Collaborate with multiple teams within Cerebras, including architecture, research, and product ...

We are seeking a Data Science Manager to translate data into the actionable insights and algorithms ... Drive innovation by staying current with emerging research, technologies, and industry best ...

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Algorithm Research information

What are the key skills and qualifications needed to thrive as an Algorithm Researcher, and why are they important?

To excel as an Algorithm Researcher, you need a strong background in mathematics, computer science, and algorithm design, often supported by an advanced degree such as a master's or PhD. Proficiency with programming languages (like Python, C++, or Java), machine learning frameworks, and version control systems is essential. Analytical thinking, creativity, and effective communication are crucial soft skills that set top performers apart in this field. These skills are vital for developing innovative, efficient solutions and collaborating within interdisciplinary teams to solve complex computational problems.

What are the typical challenges faced by professionals in Algorithm Research roles and how can they best address them?

Algorithm Research professionals often encounter challenges such as bridging the gap between theoretical solutions and practical implementation, staying updated with rapid advancements in the field, and collaborating with cross-functional teams to integrate research outcomes into real-world products. To address these challenges, it is helpful to maintain strong communication with engineering teams, participate in continual learning through academic papers and conferences, and adopt an iterative approach to testing and refining algorithms. Building a habit of documenting experiments and results also streamlines collaboration and future development.

What is Algorithm Research?

Algorithm research involves studying, designing, analyzing, and optimizing algorithms to solve complex problems efficiently. Researchers in this field explore new computational methods, improve existing algorithms, and evaluate their performance in various contexts. This work is fundamental in areas like computer science, artificial intelligence, data science, and cryptography, driving technological advances and innovation.

What is the difference between Algorithm Research vs Data Scientist?

AspectAlgorithm ResearchData Scientist
Required CredentialsAdvanced degrees in CS, Mathematics, or related fieldsDegree in CS, Statistics, or related fields; certifications like SAS or Python
Work EnvironmentResearch labs, R&D departments, academiaBusiness environments, analytics teams, tech companies
Industry UsageDeveloping new algorithms, theoretical researchAnalyzing data, building predictive models, insights generation
Common Search/ComparisonYesNo

Algorithm Research focuses on developing and testing new algorithms, often in research or academic settings, requiring advanced technical credentials. Data Scientists analyze data to generate insights and build models, working primarily in business environments. While both roles involve data and programming, their core objectives and work settings differ significantly.

What job categories do people searching Algorithm Research jobs in Toronto, ON look for? The top searched job categories for Algorithm Research jobs in Toronto, ON are:
Infographic showing various Algorithm Research job openings in Toronto, ON as of May 2026, with employment types broken down into 1% Internship, 88% Full Time, and 11% Part Time. Highlights an 12% Physical, 24% Hybrid, and 64% Remote job distribution.
Staff Data Scientist

Other

Posted 23 days ago


Job description

About Clutch:

Clutch is Canada's largest online used car retailer, delivering a seamless, hassle-free car-buying experience to drivers everywhere. Customers can browse hundreds of cars from the comfort of their home, get the right one delivered to their door, and enjoy peace of mind with our 10-Day Money-Back Guarantee... and that's just the beginning.

Named one of Canada's top growing Companies two years in a row and also awarded a spot on LinkedIn's Top Canadian Startups list, we're looking to add curious, hard-working, and driven individuals to our growing team.

Headquartered in Toronto, Clutch was founded in 2017. Clutch is backed by a number of world-class investors, including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca.

About the role:

Clutch is hiring a Staff Data Scientist to lead major improvements to our pricing algorithms and applied machine learning systems.

This is a high-ownership role for someone who thrives in ambiguity, can go deep on research and modeling, and has a track record of deploying ML to production with measurable business impact. You'll work on ML systems that already drive real outcomes - including pricing models that purchase >$1M of vehicles per day with no human intervention - with significant opportunity to take them to the next level as we scale.

You'll join a small, high-leverage data team where your work will be visible, measurable, and business-critical, with the chance to expand into additional high-impact ML domains like lending, logistics optimization, fraud detection, and recommendations. In this role, you'll own problem areas end-to-end from identifying opportunities and shaping the approach, to shipping production models and driving measurable improvements in margin and conversion.

What you'll do:

  • Own and drive improvements to Clutch's pricing algorithms, balancing margin, conversion, and customer experience.
  • Deep-dive into market and vehicle data to identify the key relationships between vehicle attributes, market dynamics, and pricing outcomes.
  • Build, validate, and deploy ML models and algorithms into production - and iterate quickly based on real-world performance.
  • Lead feature engineering, model evaluation, and experimentation design.
  • Partner with Product, Engineering, Strategy & Ops, Sell-To-Clutch & Retail to prioritize the highest-impact opportunities.
  • Contribute to additional applied ML domains as needed, including:
    • Financing / lending decisioning
    • Fraud detection
    • Search and discovery optimization
    • Vehicle recommendations / personalization

What we're looking for:

  • 8+ Years of Experience: A proven track record as a Data Scientist, with a history of delivering measurable business impact through machine learning.
  • 0-to-1 Strategic Autonomy: Proven ability to navigate high-ambiguity environments. You own the roadmap by evaluating the data, identifying untapped opportunities, and formulating your own research theories.
  • End-to-End Technical Ownership: Deep Python proficiency with the ability to own the entire lifecycle: from raw data exploration and feature engineering to model architecture and production deployment.
  • Production-Grade ML: Strong experience building and deploying traditional ML algorithms into live environments, ensuring they are robust, scalable, and maintainable.
  • Foundational Rigor: Strong statistical fundamentals and a disciplined approach to validation. You ensure that every model is built on a foundation of sound logic and clean data, maintaining high standards for accuracy and reliability without external oversight.
  • Excellent Communication: Able to bridge the gap between complex technical findings and business ROI. You can distill "black box" complexity into clear trade-offs and actionable recommendations for business leaders.