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Data Science Jobs in Calgary, AB (NOW HIRING)

Krux Analytics Inc.

Data Architect

Calgary, AB · On-site +1

Bachelor's Degree (Computer Science, Technology, Engineering, or related field) * 10+years of experienceas a data analyticsdeveloperor engineer * 5+ years of experience in developing dataarchitecture ...

Mount Royal University

Data Engineer

Calgary, AB

Qualifications A Bachelor degree-preferably in computer science, computer/software engineering or other relevant programs within data engineering, data analysis, artificial intelligence, or machine ...

Krux Analytics

Data Architect

Calgary, AB · On-site

Bachelor's Degree (Computer Science, Technology, Engineering, or related field) * 10+ years of experience as a data analytics developer or engineer * 5+ years of experience in developing data ...

ALS

Geodata Scientist

Calgary, AB · Remote

D. in Geophysics, Geology, Geological Engineering, Mineral Engineering, Data Science, Computer Science, or a related discipline. * Professional registration in relevant jurisdiction. (P.Geo, P.Eng ...

PwC

AI & Advanced Analytics, Senior Manager

Calgary, AB · On-site

CA$168K - CA$218K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

E Source

AI / ML Engineer

Calgary, AB · Remote

Collaborating with data scientists and software engineers, you'll contribute to the development of cutting-edge ML and AI products that support our mission of building a sustainable future with ...

Enfinite

Data Engineer, Digital Systems

Calgary, AB · Hybrid

A bachelor's degree in computer science, data engineering, electrical engineering, or a related field. * At least three years of hands-on data engineering experience. * Strong Python skills ...

KPMG

Data Support Senior Consultant

Calgary, AB

Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information Systems, Data Engineering, Data Analytics, or other IT-related degree; * Strong database proficiency (e.g ...

WSP

Intermediate Spatial Ecologist

Calgary, AB · On-site +1

CA$43.90 - CA$60.40/hr

Master's degree in Ecology, Data Science, Environmental Science, or a related field. * 5-10 years of relevant experience in applied spatial ecology or environmental consulting. * Strong proficiency ...

WSP

Intermediate Spatial Ecologist

Calgary, AB · On-site +1

CA$43.90 - CA$60.40/hr

Master's degree in Ecology, Data Science, Environmental Science, or a related field. * 5-10 years of relevant experience in applied spatial ecology or environmental consulting. * Strong proficiency ...

Strathcona Resources Ltd

Data Analyst

Calgary, AB

We are seeking a skilled Contract Data Analyst to join our Analytics team in Calgary for an 18-month term. Reporting to the Team Lead, Analytics, you will work closely with internal stakeholders and ...

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All JobsData Science JobsData Science Jobs in Calgary, AB

Data Science information

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

What are the key skills and qualifications needed to thrive as a data scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs

What are the most commonly searched types of Data Science jobs in Calgary, AB?

The most popular types of Data Science jobs in Calgary, AB are:

What are popular job titles related to Data Science jobs in Calgary, AB?

For Data Science jobs in Calgary, AB, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Calgary, AB look for?

The top searched job categories for Data Science jobs in Calgary, AB are:

What cities near Calgary, AB are hiring for Data Science jobs?

Cities near Calgary, AB with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Calgary, AB as of August 2026, with employment types broken down into 100% Full Time. Highlights an 50% In-person, and 50% Remote job distribution.

Machine Learning Engineer

CGG Services (Canada) Inc.

Calgary, AB • On-site

$90 - $120/hr

Other

Re-posted 9 days ago

Job description

Machine Learning Engineer

Location: Calgary, AB, Canada. Full-time.

Company Description

Viridien is a global technology and HPC leader that provides data, products, services and solutions in Earth science, data science, sensing and monitoring. Our unique portfolio supports our clients in efficiently and responsibly solving complex digital, energy transition, natural resource, environmental, and infrastructure challenges for a more sustainable future.

Job Description

Viridien is looking for a Machine Learning (ML) Engineer to help us create artificial intelligence systems and tools. You will develop machine learning models and retrain systems, contributing ideas and driving innovation to maintain our outstanding leadership position.

Preferred Education
  • Degree in Computer Science, Mathematics, Physics, Electrical Engineering, or other related technical disciplines.
Key Skills & Competencies
  • Passion and aptitude for programming and technology
  • Enthusiasm for analytical and problem-solving challenges
  • Strong enterprise project experience with Machine Learning and AI
  • Strong programming skills in C, C++, R, Java, Python
  • Good experience with Large Language Model technologies
  • Experience within Data Engineering/Data Structuring
  • Experience creating Machine Learning Algorithms and/or Libraries
  • Proven experience with deep learning frameworks and usage of DL libraries (TensorFlow/PyTorch)
  • Proficiency to design, build, test, and support innovative solutions
  • Ability to define and manage project deadlines and balance workloads across a wide variety of projects
  • Effective communication skills to keep all stakeholders regularly informed on progress
  • Drive to innovate and have fun through collaboration and generation of ideas which lead to enhancements of our workflows
  • Enthusiastic attitude towards learning and flexibility to adapt to new challenges or changes in direction
Other Skills/Experience
  • Data Visualization
  • Predictive Analysis
  • Statistical Modeling
  • Data Mining
  • Clustering & Classification
  • Data Analytics
  • Quantitative Analysis
  • Web Scraping
  • Model Development
Responsibilities
  • Design machine learning systems
  • Collaborate with stakeholders and technology team to efficiently develop AI solutions
  • Research and implement appropriate ML algorithms and tools
  • Develop machine learning applications according to requirements
  • Provide support to achieve successfully deployed models at conclusion of projects
  • Plan and manage data analysis workflows
  • Create charts, graphs, maps, and data visualization tools to provide an accessible way to see/understand trends, patterns, outliers, in data
  • Select appropriate datasets and data representation methods
  • Run machine learning tests and experimentsTrain and retrain systems when necessary
  • Extend existing ML libraries and frameworks
Equal Employment Opportunity

We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.

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