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Entry Level Data Scientist Machine Learning Jobs in British Columbia

Data Scientist

Mcleese Lake, BC

CA$102K - CA$128K/yr

Training machine learning models on observational data sets from sensors and assays in the mine and mills. * Conducting exploratory data analyses to discover opportunities for process improvements ...

Data Scientist

Mcleese Lake, BC · On-site

CA$102K - CA$128K/yr

Position Title Data Scientist, Technical Services Employment Type Full-Time Organization Gibraltar ... Training machine learning models on observational data sets from sensors and assays in the mine and ...

Training machine learning models on observational data sets from sensors and assays in the mine and mills. * Conducting exploratory data analyses to discover opportunities for process improvements ...

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

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

Applying Data Science and Machine Learning best practices to develop robust models and support data-driven decision-making across business domains * Applying machine learning and data science ...

Applying Data Science and Machine Learning best practices to develop robust models and support data-driven decision-making across business domains * Applying machine learning and data science ...

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 ...

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 ...

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Entry Level Data Scientist Machine Learning information

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 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 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 British Columbia?

The most popular types of Data Scientist Machine Learning jobs in British Columbia are:

What are popular job titles related to Entry Level Data Scientist Machine Learning jobs in British Columbia?

For Entry Level Data Scientist Machine Learning jobs in British Columbia, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Scientist Machine Learning jobs in British Columbia look for?

The top searched job categories for Entry Level Data Scientist Machine Learning jobs in British Columbia are:

What cities in British Columbia are hiring for Entry Level Data Scientist Machine Learning jobs?

Cities in British Columbia with the most Entry Level Data Scientist Machine Learning job openings:

Infographic showing various Entry Level Data Scientist Machine Learning job openings in British Columbia as of June 2026, with employment types broken down into 91% Full Time, 7% Part Time, 1% Temporary, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Scientist

Mcleese Lake, BC

CA$102K - CA$128K/yr

Full-time

Re-posted 29 days ago


Job description

Position Title

Data Scientist, Technical Services

Employment Type

Full-Time

Organization

Gibraltar Mine

Location

Mcleese Lake, BC

Reporting Relationship

Senior Engineer, Process Control

Salary Range

$102,700 to $128,300

About Trekor

Headquartered in Vancouver, British Columbia (BC), Canada, Trekor Metals Limited (Trekor) is a leading North American copper producer with a robust development pipeline of minerals projects and properties in Canada and the United States.

Known for seeing opportunities where other mining companies do not, Trekor has a two-decade track record of delivering value for shareholders, employees, communities where we operate, and others — from acquiring the Gibraltar Mine in BC for a single dollar and building it into Canada's second-largest copper producer, to transforming Arizona’s Florence Copper into the world's first greenfield in-situ copper recovery operation.

Trekor goes Beyond Potential.

For more information visit our website www.Trekormetals.com.

Role Overview

We are looking for an enthusiastic data scientist to join our technical services team. This role presents an opportunity to expand the site’s data science capabilities and support our data science lead.

Gibraltar Mine currently uses machine learning tools in our milling processes. This role’s key function would be to assist in developing and maintaining these tools by:

  • Training machine learning models on observational data sets from sensors and assays in the mine and mills.
  • Conducting exploratory data analyses to discover opportunities for process improvements, feature engineering, new targets for optimization schemes, and validating data/model health.
  • Designing reports and visualizations to communicate KPIs and insights.

The position will also support other departments by providing broader on-site data management, wrangling, analysis, and modeling to support complex mining and milling processes.

Core Responsibilities
  • Contribute to ongoing model maintenance and optimization activities for existing machine learning tools.
  • Design and implement secure, automated end-to-end data pipelines from source data to analytics-ready datasets for use in production environments.
  • Conduct exploratory data analyses and correlation studies in collaboration with the milling and mining departments.
  • Develop scalable, testable, and reliable internal data science tools, primarily in Python.