1

Chemical Engineering Data Science Jobs in Ontario

Title and Summary Director, Data Science Overview The Security Solutions Data Science team is ... and feature engineering through experimentation, validation, deployment, and monitoring. These ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Build a strong internal network across business, data science, engineering, platform, and governance partners, and share lessons learned to advance practice maturity. Required Qualifications:

CA$145K - CA$170K/yr

About the Role Robinhood's Analytics Engineering team, part of the Data Science organization, is the backbone of our decision-making ecosystem. We design and deliver foundational data products that ...

Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap ... Act as a thought leader on emerging data science techniques (personalization, recommendation ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Our client is a fintech company based out of Vancouver You Have: * 3 - 5+ Years experience working in Data Engineering/Data Science utilizing R (purrr, tidyr, dplyr, tibble, & the tidyverse) * Strong ...

Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience. Preferred: Prior experience in payments, financial services, or ...

Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap ... Act as a thought leader on emerging data science techniques (personalization, recommendation ...

CA$154K - CA$247K/yr

Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience. Preferred * Prior experience in payments, financial services, or ...

New

next page

Showing results 1-20

Chemical Engineering Data Science information

See Ontario salary details

$25.5K

$99.7K

$196K

How much do chemical engineering data science jobs pay per year?

As of Aug 29, 2026, the average yearly pay for chemical engineering data science in Ontario is $99,708.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is a chemical engineering data science?

A Chemical Engineering Data Science job combines chemical engineering principles with data science techniques to analyze and optimize chemical processes. Professionals in this field work with large datasets, machine learning models, and statistical methods to improve efficiency, reduce costs, and enhance safety in industries such as pharmaceuticals, energy, and materials. They may develop predictive models, conduct simulations, and implement AI-driven solutions to solve complex engineering challenges. This role requires expertise in programming, data analytics, and chemical process understanding to drive data-informed decision-making.

What does a chemical engineering data science do?

Professionals in Chemical Engineering Data Science typically spend their days collecting and cleaning process data, developing data models to predict or optimize chemical operations, and interpreting analytical results to improve production efficiency or product quality. They often use specialized software to simulate chemical processes and collaborate closely with engineers, plant operators, and IT professionals to implement data-driven solutions. Regular tasks may also include creating reports and data visualizations, troubleshooting data quality issues, and supporting digital transformation projects within manufacturing environments. The role is dynamic and requires continual learning as new tools and methodologies emerge, making strong communication skills and adaptability especially important.

What are the key skills and qualifications needed to thrive in chemical engineering data science?

To succeed in Chemical Engineering Data Science, you need a strong background in chemical engineering principles, statistical analysis, and programming (usually with Python, R, or MATLAB), often supported by a degree in chemical engineering or data science. Familiarity with machine learning algorithms, process simulation software (like Aspen Plus or HYSYS), and data visualization tools is highly valuable, and certifications in data analytics or Six Sigma can be advantageous. Strong analytical thinking, problem-solving, and effective communication skills help you interpret data-driven insights and collaborate with multidisciplinary teams. These competencies are essential for solving complex engineering problems, optimizing processes, and delivering actionable results in data-intensive chemical industry settings.

Can a chemical engineering data scientist become a data scientist?

A chemical engineering data scientist can become a data scientist by expanding their skills in programming, statistics, and machine learning, which are essential for general data science roles. Their domain expertise can be an advantage in industries like energy, pharmaceuticals, or manufacturing, but they may need additional training or certifications in data science tools such as Python, R, or SQL. Transitioning often involves gaining experience with broader data analysis techniques and project management skills common in data science positions.

What are the most commonly searched types of Chemical Engineering Data Science jobs in Ontario?

The most popular types of Chemical Engineering Data Science jobs in Ontario are:

What are popular job titles related to Chemical Engineering Data Science jobs in Ontario?

For Chemical Engineering Data Science jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Chemical Engineering Data Science jobs in Ontario look for?

The top searched job categories for Chemical Engineering Data Science jobs in Ontario are:

Infographic showing various Chemical Engineering Data Science job openings in Ontario as of August 2026, with employment types broken down into 77% Full Time, 9% Part Time, and 14% Contract. Highlights an 90% In-person, 4% Hybrid, and 6% Remote job distribution, with an average salary of $99,708 per year, or $47.9 per hour.

Director, Data Science

MasterCard

Toronto, ON โ€ข On-site

Full-time

Re-posted 27 days ago


Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Director, Data ScienceOverview
The Security Solutions Data Science team is responsible for delivering Artificial Intelligence (AI) and Machine Learning (ML) models that support Mastercard's Identity and risk products across the payment networks. These models are designed to be production-ready and to power high-value capabilities that protect digital transactions and enable trusted decisioning at scale.
Beyond model development, the organization is responsible for building scalable, repeatable, and resilient data science capabilities that cover the end-to-end lifecycle of machine learning solutions, from data acquisition and feature engineering through experimentation, validation, deployment, and monitoring. These systems must not only perform effectively in production, but also be built in a way that is industrialized, maintainable, and aligned with broader business and platform needs.
Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. Within this mission, the Identity Data Science portfolio plays a significant role in developing intelligence-driven solutions that improve how risk is understood and managed across the merchant lifecycle.
We are looking for a highly skilled and strategic Director to lead a Data Science team that focuses on solving merchant risk during onboarding and monitoring. This role is critical in driving the research and development of a merchant registry and profiling capability within the Identity Data Science portfolio. This includes setting the strategy for how merchant intelligence is built and scaled, guiding the development of reusable data science assets and profiling frameworks, and ensuring strong execution across product, engineering, and data science partners. You will help shape both the technical direction and operational model needed to turn this capability into a durable and scalable advantage.
Role
Key responsibilities include:
Define and execute the strategy for solving merchant risk during onboarding and monitoring through the research and development of a merchant registry and profiling capability
Lead, coach, and develop high-performing teams of Data Scientists, including hiring, mentorship, and performance management
Build a strong team culture focused on collaboration, accountability, and continuous learning
Guide the design of scalable machine learning and analytical systems using modern data and cloud platforms such as Databricks and Sparks.
Establish best practices for problem framing, technique selection, experimentation, and validation across the team
Ensure teams identify appropriate approaches for business problems and rigorously validate solutions against both technical and business outcomes
Partner closely with Product, Engineering, and other stakeholders to translate strategic needs into data science roadmaps and deliverables
Drive Agile delivery practices that support iterative development, measurable outcomes, and continuous improvement
Promote reusable data assets, standardization, and scalable workflows that strengthen long-term execution
Communicate strategy, progress, trade-offs, and business value clearly to senior leadership
Balance long-term vision with near-term delivery to maximize impact and time-to-value
All About You
Essential Skills to be successful:
Advanced degree (Master's or PhD preferred) in Data Science, ML, or related field
Extensive experience leading a Data Science team and drive innovation with inspiration.
Experienced being a great people leader but able to dig into the work where necessary
A proven track record of deploying high performance machine learning models at scale in a production environment
Strong proficiency with Python, SQL, along with experience using scalable Machine Learning and Cloud frameworks
Strong ability to guide teams in identifying appropriate techniques and validating solutions rigorously
Critical thinking and a drive to produce high-quality work, ensuring that all solutions meet rigorous standards
Demonstrated success translating complex business problems into strategic data science initiatives. Ability to lead through ambiguity and change
Strong understanding of Agile methodologies, with the ability to drive iterative delivery across cross-functional teams
Excellent stakeholder management, communication to both technical and non-technical audiences, and leadership skills
Proven ability to build teams, influence roadmaps, and deliver measurable business value in complex environments
High-energy and self-driven orientation
Nice to Have
Experience building or scaling shared data science platforms, registries, or enterprise data assets
Familiarity with merchant risk, fraud, or identity ecosystems
Experience driving cross-team standardization and reusable capabilities
Exposure to governance frameworks for model validation and AI systemsMastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility


All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

  • Abide by Mastercard's security policies and practices;

  • Ensure the confidentiality and integrity of the information being accessed;

  • Report any suspected information security violation or breach, and

  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This is a pipeline posting for future opportunities within our team.

Pay Ranges

Vancouver, Canada: $154,000 - $247,000 CADToronto, Canada: $154,000 - $247,000 CAD