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Remote Data Jobs in Toronto, ON (NOW HIRING)

Epistemix

Data Scientist

Toronto, ON · Remote

The Data Scientist supports data integration and modeling for a portfolio of customers, supporting ... We are fully remote, with team members in the United States and Europe. Benefits include: * Equity ...

Tiny Health

Microbiome Data Scientist

Toronto, ON · Remote

The Opportunity We're looking for a data scientist who is passionate about early-life gut health ... Remote-first, real overlap Our FTEs are based in North America and work core hours from 9am-6pm CST ...

Mercor

Data Scientist - AI Evaluation

Toronto, ON · Remote

CA$100 - CA$150/hr

Remote Role Responsibilities * Design precise, task-specific grading criteria for data science deliverables. This includes exploratory data analyses , statistical modeling work , machine learning ...

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Remote Data information

What are remote data jobs?

Remote data jobs are positions that involve collecting, analyzing, managing, or interpreting data while working from a location outside the traditional office environment. These roles can include data analysts, data scientists, data entry specialists, and database administrators, among others. Remote data professionals use online tools and platforms to access and process data, collaborate with teams, and deliver insights or reports. This flexible work arrangement allows individuals to contribute to data-driven projects from anywhere with an internet connection.

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a background in data science or a related field. Familiarity with data analysis tools such as Python, R, SQL, and platforms like Tableau or Power BI, along with relevant certifications, is typically required. Excellent self-motivation, time management, and communication skills help you stand out in a remote environment. These capabilities are crucial for delivering accurate insights, collaborating effectively from a distance, and meeting business objectives efficiently.

What are some common challenges faced when working as a remote data analyst, and how can they be addressed?

Remote Data Analysts often face challenges such as maintaining effective communication with team members, managing access to secure data, and staying aligned with project goals across different time zones. These can be addressed by leveraging collaboration tools like Slack or Microsoft Teams, following strict data security protocols, and participating in regular virtual meetings to ensure everyone is on the same page. Proactive communication and strong organizational skills are key to thriving in a remote data role.

What is the difference between Remote Data vs Remote Data Analyst?

AspectRemote DataRemote Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of databases and data toolsBachelor's in Data Science, Statistics, or related; proficiency in data analysis tools like Excel, SQL, and visualization software
Work EnvironmentRemote, often independent, with collaboration via online platformsRemote, involves analyzing data sets, creating reports, and communicating findings
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceBusiness, marketing, finance, and tech sectors

Remote Data generally refers to roles focused on managing and processing data, while Remote Data Analyst emphasizes analyzing data to generate insights. Both roles often require similar educational backgrounds and work remotely, but Data Analysts typically focus more on interpreting data and creating reports for decision-making.

Are there actually remote data entry jobs?

Yes, remote data entry jobs are available and involve inputting information into digital systems from a home or remote location. These roles typically require basic computer skills, attention to detail, and often use tools like spreadsheets or data management software. They are commonly offered as part-time or flexible schedules and are suitable for individuals seeking remote work opportunities.

Are there real remote data entry jobs?

Yes, remote data entry jobs are available and involve inputting information into digital systems from home. These roles typically require basic computer skills, attention to detail, and sometimes familiarity with spreadsheet or database software. They are often part-time or flexible positions, suitable for individuals seeking remote work opportunities.

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

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

What are popular job titles related to Remote Data jobs in Toronto, ON?

For Remote Data jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Remote Data jobs in Toronto, ON look for?

The top searched job categories for Remote Data jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Remote Data jobs?

Cities near Toronto, ON with the most Remote Data job openings:

Remote Data jobs near you
Infographic showing various Remote Data 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, 4% Hybrid, and 12% Remote job distribution.

Senior Data Engineer - Machine Learning & Data Platforms - REMOTE

Talent To Hire Inc.

Toronto, ON • Remote

Full-time

Re-posted 9 days ago

Job description

Senior Data Engineer- Machine Learning & Data Platforms | Remote

Our client is building the next generation of industrial intelligence, transforming complex automotive and industrial data into real-time, actionable insights powered by machine learning. This is a FT remote position. You can work from Toronto, Ottawa or Montreal.

We are seeking an experienced Data Engineer who thrives in high-scale, production ML environments and enjoys working with complex, messy datasets to build reliable, scalable data foundations for advanced analytics.

You will join a team of 13 engineers and data professionals, working in a highly collaborative, fast-moving environment. The role is remote-friendly, with strong cross-functional interaction across engineering, data science, and business teams.

What You’ll Do

  • Design, build, and maintain scalable data pipelines and ETL processes for large structured and unstructured datasets

  • Develop and optimize Spark-based data workflows supporting production ML systems

  • Collaborate closely with data scientists, ML engineers, and business stakeholders

  • Translate complex business needs into scalable, production-grade data solutions

  • Build feature engineering pipelines for time-series and predictive models

  • Ensure data quality, governance, security, and reliability across systems

  • Continuously improve data architecture, performance, and scalability

What You Bring

  • Min. 6+ years in data engineering or ML data pipeline development

  • Strong experience with Apache Spark, PySpark, Databricks, Delta Lake

  • Advanced skills in Python, SQL, and Airflow

  • Deep understanding of Medallion architecture and ETL design patterns

  • Experience building time-series features (rolling windows, lags, trend indicators)

  • Ability to work closely with ML teams and translate data into model-ready structures

  • Bachelor’s or Master’s in Computer Science, Engineering, or related field

⭐ Preferred Experience - we will highly consider candidates with below skills;

  • Background in retail, e-commerce, or supply chain environments dealing with large, messy, high-volume datasets

  • Experience working directly with machine learning teams or supporting ML model development

  • Hands-on experience in forecasting, demand planning, or similar data-heavy business domains

  • Experience integrating data from ERP/CRM/WMS systems (SAP, Oracle, legacy platforms)

  • Exposure to feature stores or ML training/serving consistency frameworks

  • Experience with IBM DataStage or legacy ETL modernization projects

  • Experience scaling distributed ML or time-series models in production environments

Why This Role

This is a strong fit for someone who enjoys working in complex, real-world data environments, especially with messy, high-volume retail-style data and close collaboration with ML teams. Retail or similar domains are highly valued.

APPLY: sasha@talenttohire.com