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Temporary Data Scientist Machine Learning Jobs in Vancouver, BC

Data Scientist II

Burnaby, BC · On-site

CA$128K - CA$144K/yr

The Trust Machine Learning team protects Remitly's customers by developing intelligent systems that prevent fraud. These systems assess the risk of every transaction and customer interaction, while ...

Senior Machine Learning Engineer

Burnaby, BC · On-site

CA$168K - CA$210K/yr

Partner with data scientists, product owners, and engineers across verticals to turn prototypes ... Machine Learning systems in production. * Strong programming skills in Python, Go, Scala or a ...

As an Applied scientist, you will provide machine learning leadership to the team that helps ... data You will help us innovate different ways to enhance tax classification experience for our ...

Master's degree or higher in Computer Science, Engineering or related field * 3+ years of machine ... and data-driven innovation? Join Weir Motion Metrics and make a lasting impact on some of North ...

... machine learning, statistical analysis, and spatial data integration techniques to support ... Assurer la mise a jour des feuilles de temps et des activites de developpement des affaires a ...

Showing results 21-40

Temporary Data Scientist Machine Learning information

What does a temporary data scientist specializing in machine learning do?

A Temporary Data Scientist specializing in Machine Learning is responsible for designing, building, and deploying machine learning models to analyze data and generate insights, but works on a contract or short-term basis. Their duties often include data preprocessing, model selection and validation, and communicating results to stakeholders. They may also be tasked with automating processes, cleaning large datasets, and collaborating with other teams to implement solutions. The temporary nature of the job means they often focus on specific projects or provide support during peak periods.

What are the key skills and qualifications needed to thrive as a temporary data scientist specializing in machine learning?

To thrive as a Temporary Data Scientist Machine Learning, you generally need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data visualization tools (like Tableau), machine learning libraries (such as scikit-learn, TensorFlow, or PyTorch), and version control systems (e.g., Git) is typically required. Strong problem-solving abilities, adaptability, and effective communication are crucial soft skills for collaborating with teams and translating technical findings to stakeholders. These skills ensure that temporary data scientists can quickly contribute actionable insights, drive data-driven decisions, and add value within a limited time frame.

What are some typical projects or tasks a temporary data scientist specializing in machine learning might work on?

As a temporary Data Scientist focusing on machine learning, you can expect to work on short-term, high-impact projects such as building predictive models, cleaning and preparing data, or developing automated analytics solutions. You may be brought in to support ongoing initiatives, provide expertise for a specific project phase, or help accelerate a backlog of tasks. Collaboration is common, and you'll likely work closely with data engineers, business analysts, and domain experts to understand requirements and deliver actionable insights within tight deadlines. This role offers exposure to diverse datasets and tools, and is an excellent opportunity to rapidly expand your experience and network.

What is the difference between Temporary Data Scientist Machine Learning vs Temporary Data Analyst?

AspectTemporary Data Scientist Machine LearningTemporary Data Analyst
Required CredentialsBachelor's/Master's in Data Science, Computer Science, or related fields; knowledge of ML algorithmsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentProject-based, collaborative teams, tech-focused companiesBusiness units, reporting teams, data-driven departments
Employer & Industry UsageTech firms, finance, healthcare, e-commerceRetail, marketing, finance, consulting

Temporary Data Scientist Machine Learning roles focus on developing and deploying machine learning models, requiring advanced analytics skills. Temporary Data Analysts primarily interpret data, generate reports, and support decision-making. While both roles involve data handling, Data Scientists with ML expertise work on predictive modeling, whereas Data Analysts focus on descriptive analytics. The choice depends on the project needs and skill requirements.

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 Temporary Data Scientist Machine Learning jobs in Vancouver, BC?

For Temporary Data Scientist Machine Learning jobs in Vancouver, BC, the most frequently searched job titles are:

What job categories do people searching Temporary Data Scientist Machine Learning jobs in Vancouver, BC look for?

The top searched job categories for Temporary Data Scientist Machine Learning jobs in Vancouver, BC are:

Infographic showing various Temporary Data Scientist Machine Learning job openings in Vancouver, BC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Senior Machine Learning Engineer - AI Platform

Workday

Vancouver, BC • On-site

Full-time

Posted 29 days ago


Workday rating

7.6

Company rating: 7.6 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

158th of 247 rated software companies


Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

Do you want to build AI-powered software that impacts millions of people every day? The AI Core team, part of Workday's AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems. Our work delivers critical AI platform capabilities and differentiated, deep-value agent applications.

About the Role

As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG. You will collaborate with other engineers to deliver ML solutions across Workday's product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised. Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday's vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?

You are a strong technical leader with deep Python expertise and solid software engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently. Specifically, you will:

  • Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services.
  • Be responsible for evaluation, scalability and observability of these features.

  • Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures

  • Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

  • Serve as a technical role model for more junior engineers

About You

Basic Qualifications:

  • Bachelor's (Master's or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent

  • 6+ yrs experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation

  • 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models

  • 5+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)

Other Qualifications:

  • 3+ years of experience in building information retrieval systems and/or graph-based recommendation systems.

  • 3+ years of hands-on professional experience in developing large language models (LLMs), text generation models, or graph-based machine learning models for production, including data processing, model fine-tuning, model deployment and model evaluation

  • 3+ years of experience building services to host machine learning models in production at scale

  • 3+ years of experience in machine learning and deep learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn

  • 3+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker

  • Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases

  • Professional experience in independently solving ambiguous, open-ended problems and technically leading teams


Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: USA.CO.Boulder


Primary Location Base Pay Range: $171,600 USD - $257,400 USD


Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD

Additional Considerations:

The application deadline for this role is the same as the posting end date stated as below:

08/31/2026


Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.


What Workday employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005