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Remote Data Science Jobs in Ontario (NOW HIRING)

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

Role Overview As a Senior Credit Risk Modeling - Data Science, you will be an individual ... Flexible work model (hybrid/remote options). * Learning budget, health benefits, and team culture ...

Directly to the Manager, Data Science and Analytics Location: Fully remote within Canada and some domestic travel may be required. Must be flexible for evening/weekend commitments as needed. Job Type ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

This is a permanent position that is completely remote! Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R ...

Machine learning, data science, AI engineering, or applied analytics experience in industry or an ... A flexible work environment combining in office collaboration and remote working * Competitive time ...

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Showing results 1-20

Remote Data Science information

See Ontario salary details

$23.5K

$104.5K

$199.5K

How much do remote data science jobs pay per year?

As of Jun 13, 2026, the average yearly pay for remote data science in Ontario is $104,540.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,000.00 and $145,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Scientist, and why are they important?

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, often supported by a relevant degree. Expertise in programming languages such as Python or R, familiarity with machine learning libraries, and experience with cloud-based data platforms are typically required. Excellent communication, self-motivation, and time management skills help you effectively collaborate and deliver results in a remote environment. These skills ensure accurate data analysis, meaningful insights, and successful teamwork despite physical distance.

How do remote data scientists typically collaborate with cross-functional teams to deliver insights?

Remote data scientists often work closely with product managers, engineers, and business analysts using digital collaboration tools such as Slack, Zoom, and project management platforms. Regular virtual meetings, code sharing via Git repositories, and clear documentation are essential to ensure alignment and transparency. While working remotely can present challenges in communication, proactive updates and scheduled syncs help foster strong teamwork and keep projects on track.

What is remote data science?

Remote data science refers to the practice of performing data analysis, modeling, and interpretation tasks from a location outside of a traditional office, such as from home or a co-working space. Remote data scientists use tools like Python, R, and SQL to analyze data, build predictive models, and communicate insights to stakeholders, all while collaborating virtually with their teams. This setup offers flexibility and can increase access to global job opportunities, but also requires strong self-motivation and communication skills to be effective.

Can a data scientist work fully remote?

Yes, many data scientists work fully remote, especially in companies that prioritize flexible work arrangements. Remote data science roles often require strong communication skills, proficiency with collaboration tools, and the ability to work independently on projects using programming languages like Python or R. However, some positions may require occasional in-person meetings or on-site presence depending on company policies.

Is 40 too late for data science?

Age is not a barrier to entering data science, and many professionals start or transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists will continue to be essential for developing complex algorithms, understanding business context, and ensuring ethical use of AI tools. Skills in programming, statistical analysis, and machine learning remain critical for the profession's evolving landscape.

What Are the Qualifications to Get a Remote Data Science Job?

The qualifications for a remote data scientist depend in large part on your employer and their industry. Most employers expect remote data science professionals to have at least a bachelor’s degree in statistics, math, computer science, or a related field. Some expect postgraduate degrees in a field like data mining or machine learning or demonstrable skills in these areas. As a remote worker, you need access to relevant programs and an internet connection. You may also want to pursue certification, such as becoming a Certified Analytics Professional (CAP).

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

AspectRemote Data ScienceRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; programming skills in Python/R; knowledge of machine learningDegree in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves building models and algorithmsData reporting, visualization, and interpreting data trends for decision-making
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, retail, finance, healthcare

Remote Data Science involves developing predictive models and advanced analytics, requiring programming and machine learning skills. Remote Data Analysts focus on interpreting data, creating reports, and visualizations. While both roles analyze data remotely, Data Scientists typically handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and reporting.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.
What are the most commonly searched types of Data Science jobs in Ontario? The most popular types of Data Science jobs in Ontario are:
What are popular job titles related to Remote Data Science jobs in Ontario? For Remote Data Science jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Remote Data Science jobs in Ontario look for? The top searched job categories for Remote Data Science jobs in Ontario are:
What cities in Ontario are hiring for Remote Data Science jobs? Cities in Ontario with the most Remote Data Science job openings:
Infographic showing various Remote Data Science job openings in Ontario as of June 2026, with employment types broken down into 2% As Needed, 63% Full Time, 29% Part Time, 4% Temporary, and 2% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $104,540 per year, or $50.3 per hour.
Data Scientist II

Other

Posted 5 days ago


Job description

As a Data Scientist II, you will leverage theory, data, and research to solve business problems. You will support data science and analytics efforts across multiple areas of the business including Sales, Marketing, Finance, HR, and related functions. You will contribute to building and improving measurement and reporting processes. To this end, you will help teams access insights needed to operate effectively.

This role will be responsible for drawing insights from large data sets, defining and implementing key model performance indicators, and for communicating insights and trends to support business decision-making, as it relates to data science-enabled decisions. This role will work with datasets relevant to assigned projects and business areas and be responsible to work closely with business stakeholders on measurement, success metrics, and analytics. Effectiveness in this position will require an understanding of technical methods and data engineering necessary to build and implement data science models, as well as knowing general industry trends, business objectives, and workforce dynamics. You will use data to develop insights, forecasts, metrics, dashboards and recommendations to inform decisions about our operations and go-to-market strategy.

 

What You'll Do (Essential Functions) 
  • Contribute to data science projects supporting Sales, Marketing, Finance, HR, and related functions, collaborating with other team members.
  • Apply an understanding of business operations to translate defined requirements into data science tasks and KPIs, and identify opportunities where data science can support team objectives.
  • Translate and summarize data into written reports, tables, graphs, dashboards, and charts to convey findings to the team and immediate stakeholders.
  • Perform data preprocessing, feature engineering, and model selection for routine problems, working independently on well-defined or ambiguous tasks.
  • Design and implement AI models and pipelines based on documented requirements, and analyze model performance using standard evaluation metrics.
  • Use distributed processing systems (e.g., Snowflake, Databricks, Google Cloud Platform) to handle datasets of increasing size and complexity.
  • Proactively identify and resolve issues in pipeline development and deployment.
  • Write understandable, modular code by applying established software development practices and style guides.
  • Use common data science libraries to implement designed solutions efficiently.
  • Participate in code reviews at critical points to validate that code meets requirements and standards, and create initial technical documentation.

The information in this job description represents a summary of the role and is not intended to be a comprehensive list of job duties. Responsibilities and duties of the position may change without notice at the Company's discretion.

 

What You Bring (Required Qualifications)
  • Master's degree in a STEM or quantitative field (statistics, computer science, mathematics, economics, engineering, or related).
  • 2+ years of professional experience building and deploying data science or machine learning solutions, including at least one production deployment.
  • Demonstrated experience translating business questions into data science problems and communicating findings to technical and non-technical audiences.
  • Proficiency in Python and SQL, and experience with data visualization tools such as Tableau.
  • Experience working with cloud data and ML platforms such as Snowflake, Databricks, or Google Cloud Platform.
  • Working knowledge of applied statistical methods and machine learning techniques (e.g., regression, classification, time series, cross-validation, model evaluation).

 

Preferred Qualifications
  • Doctoral degree in a STEM or quantitative field (statistics, computer science, mathematics, economics, engineering, or related).
  • Familiarity with MLOps practices - model versioning, monitoring, drift detection, CI/CD for ML.
  • Experience designing and maintaining dashboards for operational or executive audiences.
  • Experience presenting analyses to senior technical and non-technical audiences.
  • Exposure to Sales, Marketing, Finance, or HR analytics domains.

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