Top Data Science Jobs to Apply in Canada

Check out these exciting roles at top companies like Clarivate, Mastercard, and more
Data Science Jobs
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Data Science has become one of the most sought-after fields in the tech industry. Companies are constantly on the lookout for skilled data scientists who can help them make data-driven decisions and enhance their business outcomes. In Canada, several top-tier organizations, including Clarivate, Mastercard, Gore Mutual Insurance, Lyft, and Ample Insight Inc., are currently hiring data scientists. This article highlights key opportunities and responsibilities for data science jobs across these companies.

1. Clarivate - Data Scientist: Academia & Government Markets (Toronto, ON)

Clarivate is looking for a Data Scientist to work on projects focused on improving the user experience for their Academia & Government Markets (A&G) data and websites. The role involves researching and implementing machine learning (ML) and natural language processing (NLP) algorithms to solve specific business challenges.

Key Responsibilities:

  • Research and identify ML and NLP methods to enhance user experience.

  • Implement these methods and create test plans to validate the models.

  • Explore new applications of ML and NLP within Clarivate’s extensive data sets.

  • Discover insights from existing data and recommend additional data sources.

This role requires a strong understanding of ML and NLP techniques, with an emphasis on problem-solving in the context of academia and government data. It’s a great opportunity for data scientists looking to make a meaningful impact on user experiences in these markets.

Apply here.

2. Mastercard - Lead Data Scientist (Vancouver, BC)

Mastercard’s Vancouver office is hiring a Lead Data Scientist to advance their fraud detection models. The ideal candidate will work closely with business owners to understand requirements and develop models for enhancing fraud detection across credit and debit card transactions.

Key Responsibilities:

  • Develop fraud detection models for credit and debit card transactions.

  • Lead the implementation of data and model development pipelines.

  • Explore fraudulent patterns and trends for feature discovery.

  • Ensure the robustness of trained models through testing and validation.

  • Enhance existing modeling practices to maintain competitiveness.

This role suits data scientists with expertise in fraud detection, model development, and deploying ML models in production. Strong collaboration skills are essential, as the candidate will interact with multiple stakeholders.

Apply here.

3. Gore Mutual Insurance - Data Scientist (12-Month Contract, Cambridge, ON)

Gore Mutual Insurance is offering a 12-month contract role for a Data Scientist to help optimize business solutions and deploy machine learning models. This position focuses on constructing pipelines for data ingestion, feature engineering, and model deployment.

Key Responsibilities:

  • Construct pipelines for algorithm-driven insights and data ingestion.

  • Apply different ML algorithms such as supervised classification and reinforcement learning.

  • Utilize optimization techniques like linear programming and dynamic programming.

  • Deploy ML models into production environments using CI/CD pipelines.

  • Communicate insights and results to business stakeholders effectively.

The role demands expertise in designing and applying AI algorithms in a business context, with a focus on data pipelines and continuous model deployment.

Apply here.

4. Lyft - Data Scientist, Algorithms (Toronto, ON)

Lyft is looking for a Data Scientist specializing in algorithms to support their operations and product development teams. This role requires using data to identify growth opportunities and create analytical frameworks to monitor business performance.

Key Responsibilities:

  • Leverage data to identify opportunities for growth and efficiency.

  • Collaborate with product managers, engineers, and other teams to translate data insights into actionable decisions.

  • Design and analyze online experiments to validate business hypotheses.

  • Establish metrics that measure the health of products and user experience.

  • Provide technical guidance and coaching to the team.

This position is ideal for data scientists who are skilled in experimentation, metrics development, and collaboration across various business functions.

Apply here.

5. Ample Insight Inc. - Data Scientist: Data Analytics and Infrastructure (Toronto, ON)

Ample Insight Inc. is seeking a Data Scientist passionate about analytics and infrastructure to help drive business decisions through data. The candidate will work with structured and unstructured data and build data workflows and schemas.

Key Responsibilities:

  • Architect ETL workflows and develop data schemas.

  • Utilize structured and unstructured data to generate actionable insights.

  • Design analytical frameworks to support data-driven decision-making.

  • Communicate insights effectively to business stakeholders.

  • Collaborate with engineering partners to optimize data pipelines.

This role requires a strong analytical mindset and experience in architecting data workflows, making it a great fit for data scientists focused on data engineering and analytics.

Apply here.

Choosing the Right Data Science Role

Each of these positions offers unique opportunities for data scientists with varying skill sets and experiences. Clarivate and Ample Insight Inc. focus more on implementing ML and NLP solutions and data analytics, while Mastercard and Gore Mutual Insurance emphasize model development and deployment for business optimization and fraud detection. Lyft, on the other hand, offers a blend of product and data science, ideal for those interested in driving business decisions through experimentation and metrics development.

Before applying, consider the following:

Area of Expertise: Select roles that align with your core competencies, whether it’s ML, NLP, fraud detection, or data engineering.

Business Context: Understanding the business implications of your role can enhance your effectiveness. For example, Mastercard focuses on fraud detection, while Lyft is more product-focused.

Project Scope: Determine if the role involves end-to-end model development or focuses on specific areas like feature engineering or data ingestion.

Location and Work Arrangement: Some roles offer contract-based positions, while others are full-time. Evaluate what suits your career plans best.

Data science continues to be a rapidly expanding field, with new opportunities emerging in diverse sectors. The roles at Clarivate, Mastercard, Gore Mutual Insurance, Lyft, and Ample Insight Inc. provide a glimpse into the varied responsibilities and skill requirements for data scientists in Canada. Each position offers a chance to contribute to meaningful projects, build robust models, and leverage data for strategic decision-making.

Explore these opportunities and apply to positions that resonate with your career goals and expertise.

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