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Data Science Jobs in Alberta (NOW HIRING)

Own all stages of the data science project lifecycle, including: Develop, deploy, monitor, and scale models through the full Software Development Life Cycle into production (including both ML and ...

Own all stages of the data science project lifecycle, including: Develop, deploy, monitor, and scale models through the full Software Development Life Cycle into production (including both ML and ...

Own all stages of the data science project lifecycle, including: Develop, deploy, monitor, and scale models through the full Software Development Life Cycle into production (including both ML and ...

D. in Computer Science, Data Science, or related quantitative field. * 3+ years experience building and deploying machine learning models in a production environment. * Expertise in Python data ...

D. in Computer Science, Data Science, or related quantitative field. * 3+ years experience building and deploying machine learning models in a production environment. * Expertise in Python data ...

Staff Data Scientist

Calgary, AB · Hybrid

CA$192K - CA$230K/yr

Architect reusable, "platform-level" forecasting frameworks to be used by other Data Science teams. High-Impact Modeling: * Own the development of "tier-1" models-those with the highest business risk ...

Senior Data Scientist

Calgary, AB · Hybrid

CA$160K - CA$184K/yr

Experience & Impact: * 5+ years of experience in Data Science, Machine Learning, or a highly quantitative field. * Demonstrated track record of deploying models that drove significant business impact ...

You will work closely with Data Analysts, Data Scientists, Business Systems Analysts, and platform teams to help deliver reliable, well-governed, and cost-effective data solutions. This position is ...

Build reliable transformation workflows that support analytics, reporting, and data science initiatives . * Monitor, troubleshoot, and optimize data infrastructure to ensure high performance ...

... Data Science, or a related role - Prior work experience in the construction industry is a strong plus - A minimum of 2 years of experience working in a reputable consulting firm is required ...

Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, or a related technical field, or equivalent practical experience. * Minimum 5 years of progressive experience in mine data ...

Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, or a related technical field, or equivalent practical experience. * Minimum 5 years of progressive experience in mine data ...

Diploma or degree in Data Analytics, Data Science, Computer Science, Business, Economics, Engineering, Accountin g , or a related field * Experience in data analysis, financial analysis, or capital ...

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Data Science information

See Alberta salary details

$23.5K

$116.9K

$210.5K

How much do data science jobs pay per year?

As of Jun 11, 2026, the average yearly pay for data science in Alberta is $116,864.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $161,000.00 per year, depending on experience, location, and employer.

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.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

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.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret complex data, develop models, and make strategic decisions. Data scientists with expertise in programming, statistical analysis, and machine learning remain essential for designing and deploying AI solutions effectively.

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 jobs are there in data science?

Data science offers a variety of roles including Data Scientist, Data Analyst, Machine Learning Engineer, Data Engineer, and Business Intelligence Analyst. These positions typically require skills in programming, statistics, and data visualization tools, and may involve working with large datasets, predictive modeling, and data-driven decision making.

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.

What jobs does a data scientist do?

A data scientist analyzes large datasets to extract insights, build predictive models, and support decision-making. They use programming languages like Python or R, employ statistical techniques, and often work with machine learning algorithms to solve complex problems across various industries.
What are the most commonly searched types of Data Science jobs in Alberta? The most popular types of Data Science jobs in Alberta are:
What are popular job titles related to Data Science jobs in Alberta? For Data Science jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Alberta look for? The top searched job categories for Data Science jobs in Alberta are:
What cities in Alberta are hiring for Data Science jobs? Cities in Alberta with the most Data Science job openings:
Infographic showing various Data Science job openings in Alberta as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $116,864 per year, or $56.2 per hour.
Senior Data Scientist

CA$90K - CA$160K/yr

Full-time

Medical, Retirement

Posted 8 days ago


S&P Global rating

8.0

Company rating: 8.0 out of 10

Based on 5 frontline employees who took The Breakroom Quiz


Job description

About the Role:

Grade Level (for internal use):

10

S&P Global Corporate

The Role: Senior Data Scientist

Location: Princeton, NJ or New York, N, or Charlottesville, VA. Toronto, ON, Calgary, AB, Mexico City, MX, London, UK (hybrid -2 days onsite per week)

The Team:

The Collection Platforms & AI team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a global team and encouraged for thoughtful risk-taking and self-initiative.

The Impact:

  • The Collection Platforms & AI team has already delivered breakthrough products and significant business value over the last 5 years.
  • In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems.

What's in it for you:

  • You will be part of a dynamic team that solves diverse problems using applied machine learning and web development with an end-to-end implementation of the solution: inception, prototyping, development, and productionizing.
  • Be a part of a global company and build solutions at enterprise scale.
  • Be a part of and grow with a highly skilled, hands-on technical team.
  • Contribute to solving high-complexity, high-impact problems end-to-end.
  • Build end-to-end production-ready pipelines from ideation to deployment.

Key Responsibilities

  • Develop and deploy large-scale ML and GenAI-powered products and pipelines.
  • Own all stages of the data science project lifecycle, including:

    Develop, deploy, monitor, and scale models through the full Software Development Life Cycle into production (including both ML and GenAI services).

    Perform exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ML and GenAI approaches.

    Partnering with business leaders, domain experts, and end-users to gather requirements and align on success metrics.

    Follow coding standards, perform code reviews, and optimize data science workflows.

    Evaluation, interpretation, and communication of results to executive stakeholders.

Technical Requirements:

  • Strong grasp of statistics, probability, and the mathematics underpinning modern AI.
    • Linear programming and optimization.
    • Multi-dimensional optimizers, such as Adam, SGD, Gradient Descent ...
    • Ability to adjust weights for full/partial tuning of LLMs.
  • Hands-on experience with any large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering,fine-tuning/customization,and embedding-based retrieval
  • Intermediate to expert proficiency in Python (NumPy, Pandas, SpaCy, scikit-learn, PyTorch/TF 2, Hugging Face Transformers).
  • Understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems.
  • Solid understanding of database structures and SQL.
  • Ability to perform independent research and synthesize current AI/ML research, with a track record of applying new methods in production.
  • Experience in end-to-end GenAI or advanced NLP projects, such as NER, table extraction, OCR integrations, or GNN solutions.
  • Familiarity with orchestration and deployment tools: Airflow, Redis,Flask/Django/FastAPI,SQL,R-Shiny/Dash/Streamlit.
  • Openness to evaluate and adopt emerging technologies and programming languages as needed.
  • Public contributions or demos on GitHub, Kaggle, StackOverflow, technical blogs, or publications.
  • 5+ years in professional work within AI space or buildingstatistical/mathematicalquantitative models in production.

Preferred Qualification

  • Advanced technical degree (Master and above) in any of Sciences, Technology, Engineering and Mathematics.
  • Experience in productionizing AI applications.
  • Experience with multi-modal LLMs and integrating vision and text for autonomous agents.

Right to work requirements for US based out Candidates:

This role is open only for candidates with indefinite right to work within the USA.

Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $90,000 - $160,000. Final base salary for this role will be based on the individual's geographical location as well as experience and qualifications for the role.
In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.

Right to work requirements for Canada based out candidates:

This role is open to candidates with indefinite right to work within Canada.

Compensation/Benefits Information: (This section is only applicable to Canadian Candidates:) S&P Global states that the anticipated range of compensation for this position is 95,000 CAD to 140,000 CAD. Final compensation for this role will be based on the individual's performance, geographic location, as well as experience level, skill set, training, licenses, and certifications. In accordance with Ontario's new regulations effective January 1, 2026, this job posting provides information on expected compensation. S&P Global will not be utilizing artificial intelligence in our hiring process. Additionally, we are committed to transparency and will inform all interviewed candidates of hiring decisions within 45 days of their interview. This posting is for an existing vacancy, and we encourage you to reach out for further information regarding our hiring practices or any questions you may have. Thank you for considering a career with us!

What's In It For You?

Our Mission:

Advancing Essential Intelligence.

Our People:

We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values:
Integrity, Discovery, Partnership


Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
Benefits:

We take care of you, so you cantake care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global.
Our benefits include:

  • Health & Wellness: Health care coverage designed for the mind and body.

  • Flexible Downtime: Generous time off helps keep you energized for your time on.

  • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

  • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

  • Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

  • Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference.

For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global:

At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

Recruitment Fraud Alert:

If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported toreportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, "pre-employment training" or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activityhere.

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Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to:EEO.Compliance@spglobal.comand your request will be forwarded to the appropriate person.
US Candidates Only:Know Your Rights: Workplace discrimination is illegal

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20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.1 - Middle Professional Tier I (EEO Job Group), SWP Priority - Ratings - (Strategic Workforce Planning)