2

Entry Level Data Scientist Machine Learning Jobs in Vancouver, BC

Title and Summary Data Scientist II Overview The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard ...

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

The Data Science team is responsible for developing advanced AI and machine learning solutions that power critical products across Mastercard's network. This role will support the merchant/acquiring ...

Data Scientist

Vancouver, BC · On-site

$80K - $100K/yr

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

Previous experience with Machine Learning, Data Science and solving problems at scale Perks: * Competitive Salary * Individual performance bonus * Health and dental benefits * 3 weeks' vacation

Variational AI is searching for a machine learning scientist to join us in our quest to radically accelerate the development of new drugs through machine learning excellence. For over six years, we ...

We are looking for a seasoned machine learning scientist to join our team at SAP Concur to deliver ... Push the frontiers of scalable applied AI with real-world data and application. * Work with ...

... machine learning, statistical analysis, and spatial data integration techniques to support ... Familiarity with geological sciences, mineral deposits, and mining/exploration. * Experience ...

... message data in the business communications domain. We have several research themes, including ... Develop, implement, and refine state-of-the-art Natural Language Processing and Machine Learning ...

next page

Showing results 1-20

Entry Level Data Scientist Machine Learning information

What are the key skills and qualifications needed to thrive as an entry level data scientist machine learning?

To thrive as an Entry Level Data Scientist in Machine Learning, you need a solid background in statistics, programming (Python or R), and foundational machine learning concepts, typically supported by a relevant degree in computer science, data science, or a related field. Familiarity with tools and libraries such as scikit-learn, TensorFlow, Pandas, and SQL, as well as experience with data visualization platforms, is highly valuable. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly set candidates apart. These skills are essential for effectively analyzing data, building predictive models, and translating complex results into actionable business insights.

What is an entry level data scientist machine learning?

Entry level data scientist machine learning jobs are positions for individuals who are new to the field of data science and machine learning. These roles typically focus on working with data, building and testing machine learning models, and supporting more experienced data scientists. Entry level professionals may clean and analyze data, implement basic algorithms, and help interpret results to inform business decisions. These jobs often require proficiency in programming languages like Python or R, foundational knowledge of statistics, and some experience with machine learning libraries.

What are some common challenges faced by entry level data scientists working with machine learning models?

Entry-level data scientists often encounter challenges such as cleaning and preparing messy or incomplete datasets, selecting appropriate algorithms for specific problems, and tuning model parameters to achieve optimal performance. In addition, they may need to clearly communicate technical findings to non-technical stakeholders and collaborate closely with team members from engineering, product, and business departments. Gaining experience in version control, reproducibility, and model deployment are also important steps in mastering the end-to-end machine learning workflow.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Vancouver, BC? The most popular types of Data Scientist Machine Learning jobs in Vancouver, BC are:
What are popular job titles related to Entry Level Data Scientist Machine Learning jobs in Vancouver, BC? For Entry Level Data Scientist Machine Learning jobs in Vancouver, BC, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Scientist Machine Learning jobs in Vancouver, BC look for? The top searched job categories for Entry Level Data Scientist Machine Learning jobs in Vancouver, BC are:
Infographic showing various Entry Level Data Scientist Machine Learning job openings in Vancouver, BC as of July 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Full-time

Re-posted 16 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

Data Scientist IIOverview
The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard's Identity and risk solutions across authentication and authorization use cases. These models are production-ready and designed to support key products and capabilities that help make digital transactions safer, smarter, and more trusted.
In addition to building models, the team is responsible for the research and development of scalable end-to-end data science capabilities covering the full lifecycle of model creation-from data extraction and feature engineering to validation, deployment, and monitoring. These capabilities must be designed to scale and to be repeatable, resilient, and industrialized so they can support long-term product growth and evolving business 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 space, the Identity Data Science portfolio plays an important role in advancing intelligence-driven solutions that enable more effective risk assessment and decisioning across the merchant lifecycle.
You will join a dynamic and innovative team working at scale with modern big data platforms and technologies. In this role, you will focus on solving merchant risk during onboarding and ongoing monitoring through the research and development of a merchant registry and profiling capability within the Identity Data Science portfolio. This includes helping build the foundational data assets, profiling logic, analytical workflows, and machine learning approaches needed to better understand merchant behavior, relationships, and risk signals over time.
Role
You will contribute to the design and development of data science capabilities that improve merchant risk assessment across onboarding and monitoring workflows.
Key responsibilities include:
Analyze large-scale transaction, merchant, and related entity data to identify patterns, trends, and anomalies
Support the research and development of a merchant registry and profiling capability to strengthen merchant risk assessment during onboarding and ongoing monitoring
Contribute to feature engineering, entity resolution, and analytical workflows that improve merchant-level intelligence
Prototype machine learning and analytical solutions under guidance from senior team members
Help build and maintain scalable data and model workflows using Databricks and Spark-based environments
Identify appropriate techniques for different analytical problems and help validate solutions through structured testing, benchmarking, and performance evaluation
Support model monitoring, benchmarking, and iterative improvement of data science solutions
Work closely with partners across Data Science, Product, and Engineering in an Agile environment to support iterative delivery and continuous improvement
All About You
Essential Skills to be successful:
Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or another quantitative discipline such as Engineering, Economics, or Physics
Experience in applying data science and machine learning to solve real business problems
Solid foundation in statistics, analytics, and core machine learning concepts
Experience with Python and SQL; familiarity with tools such as Pandas for data manipulation and analysis
Exposure to large datasets and interest in scalable data processing; familiarity with Spark is a plus
Experience with writing clean, modular, and well-documented code following Data Science best practices. Ability to collaborate effectively through code contributions, peer reviews, and shared development workflows to ensure robust, maintainable, and efficient solutions
Ability to identify appropriate analytical techniques and validate solutions through structured evaluation
Critical thinking and a drive to produce high quality work, ensuring that all solutions meet rigorous standards
Understanding of Agile methodologies, with the ability to contribute to iterative delivery
Openness to learn and apply new technologies, staying current with industry trends and advancements
Good communication skills, enabling effective collaboration with team members and stakeholders
Self-driven with a collaborative mindset and enthusiasm for learning in a fast-paced, innovative environmentMastercard 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.

Pay Ranges

Vancouver, Canada: $91,000 - $140,000 CAD