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Web Scraping Jobs in Ontario (NOW HIRING)

Web Scraping information

See Ontario salary details

$30K

$83.1K

$151K

How much do web scraping jobs pay per year?

As of Aug 2, 2026, the average yearly pay for web scraping in Ontario is $83,110.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $110,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by web scraping professionals, and how are they typically addressed?

Web scraping professionals often encounter challenges such as dealing with websites that use dynamic content loading, anti-scraping measures like CAPTCHAs, or frequent changes to site structure. To overcome these, they may use headless browsers, rotating proxies, and advanced parsing techniques to mimic human behavior and adapt quickly to site updates. Collaborating with legal and compliance teams is also important to ensure all data collection respects relevant laws and website terms of service.

What is web scraping?

Web scraping is the automated process of extracting data from websites. It involves using software tools or scripts to collect information from web pages, which can then be saved and analyzed for various purposes. Web scraping is commonly used for market research, price monitoring, data aggregation, and academic research. However, it's important to respect website terms of service and legal considerations when scraping data.

What is the difference between Web Scraping vs Data Analyst?

AspectWeb ScrapingData Analyst
Required SkillsProgramming, data extraction, scriptingData interpretation, statistical analysis, visualization
Work EnvironmentTechnical, often remote, involves codingOffice or remote, involves analysis and reporting
Tools & TechnologiesPython, BeautifulSoup, ScrapyExcel, SQL, Tableau, R
Industry UsageData collection for research, marketing, SEOBusiness insights, reporting, decision-making

Web Scraping focuses on extracting data from websites using programming skills, while Data Analysts interpret and analyze data to generate insights. Both roles require analytical thinking but differ in technical focus and end goals.

What are the key skills and qualifications needed to thrive as a Web Scraping Specialist, and why are they important?

To thrive as a Web Scraping Specialist, you need strong programming skills in languages like Python, knowledge of HTML/CSS, and an understanding of data extraction techniques. Familiarity with tools and frameworks such as BeautifulSoup, Scrapy, Selenium, and sometimes APIs or browser automation is typically required. Attention to detail, problem-solving, and ethical judgment are important soft skills that help navigate complex data sources and legal considerations. These skills ensure efficient, accurate, and compliant collection of large-scale data critical for analytics and business intelligence.

What Are Web Scraping Jobs?

Web scraping jobs involve using specialized software and web crawling tools to extract data from websites. This data is extracted for competitor analysis, market trends, pricing research, and other information that can help businesses improve their performance. As a data engineer, your responsibilities are to understand and use these tools or use manual techniques to collect information. Your duties also include creating or troubleshooting web scraping tools, analyzing the data you obtain, and passing the information on to the appropriate leaders of a company. You can find these positions with technology companies that offer web scraping services to clients.

What are popular job titles related to Web Scraping jobs in Ontario? For Web Scraping jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Web Scraping jobs in Ontario look for? The top searched job categories for Web Scraping jobs in Ontario are:
Infographic showing various Web Scraping job openings in Ontario as of July 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 57% In-person, and 43% Remote job distribution, with an average salary of $83,110 per year, or $40 per hour.

Sr. Machine Learning Engineer, Content Shopping

Pinterest

Toronto, ON • Remote

Other

Re-posted 11 days ago


Job description

With more than 535 million users around the world and 400 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3,500 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.
The Content Shopping Mining ML team builds machine learning systems that understand shopping-related content across the web, turning unstructured merchant pages into high-quality structured product data like price, title, availability, and images. This helps improve product experiences on Pinterest, including content quality, distribution, recommendations, and search; for example, see the team's KDD 2025 paper, Cross-Domain Web Information Extraction https://arxiv.org/pdf/2508.01096.

What you'll do:

  • Identify and evaluate high-value content sources for Pinterest including websites, merchants, and social media accounts
  • Help build scalable systems to acquire that content and extract structured attributes from it.
  • Partner closely with cross-functional teams across Pinterest to improve content quality and power better user experiences, such as reducing low-quality content and improving search relevance.
  • Train, fine-tune, and distill language models to better understand webpages and deploy those models in production at scale.
  • Design and build systems for managing large-scale datasets, improving data quality, and automating model iteration and improvement.
  • Use modern agentic coding tools to accelerate development, experimentation, and operational efficiency.

What we're looking for:

  • 5+ years of industry experience applying machine learning to real-world problems, such as search, ranking, recommender systems, natural language processing, personalization, reinforcement learning, or graph representation learning.
  • Hands-on experience training, evaluating, and deploying language models in production environments.
  • Strong problem-solving skills, with the ability to work autonomously, think creatively, and drive ambiguous projects forward.
  • Experience or strong interest in web crawling, web scraping, and large-scale content acquisition.

Nice to have:

  • M.S. or Ph.D. in Machine Learning, Computer Science, or a related technical field.
  • Publications in top-tier machine learning conferences.
  • Passion for applied machine learning and for building products that improve the Pinterest experience.
  • Experience with web crawling, web scraping, search, recommendation systems, or content understanding pipelines.
  • Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

Relocation Statement:

  •  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

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