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Entry Level Machine Learning Jobs in Calgary, AB

Entry Level Machine Learning information

See Calgary, AB salary details

$20K

$65.3K

$152K

How much do entry level machine learning jobs pay per year?

As of Sep 13, 2026, the average yearly pay for entry level machine learning in Calgary, AB is $65,272.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,500.00 and $82,000.00 per year, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.

What are the most commonly searched types of Machine Learning jobs in Calgary, AB?

The most popular types of Machine Learning jobs in Calgary, AB are:

Infographic showing various Entry Level Machine Learning job openings in Calgary, AB as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $65,272 per year, or $31.4 per hour.

UDA Business Analyst - Students Seeking Opportunities

Calgary, AB • On-site

ExxonMobil
Oil and Gas Extraction • 10K+ employees

Full-time

Posted 16 days ago


ExxonMobil rating

6.0

Company rating: 6.0 out of 10

Based on 232 frontline employees who took The Breakroom Quiz


Job description

At Imperial, we work every day to responsibly develop Canada’s energy resources – applying technology and innovation to supply affordable, accessible and reliable energy while reducing emissions. Imperial recognizes the important role we can play by advancing climate solutions within our operations and by providing lower life-cycle emission products to our customers. This effort is powered by a unique and diverse workforce fueled by a pride in what we do and what we stand for. 

The success of our upstream, downstream and chemical, and corporate divisions is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. 

Imperial honours diverse backgrounds so we can be a place where people can bring their full selves to work, no matter their identity, race, gender, sexual orientation, age, or ability.

At Imperial, we want you to come for the position and stay for the career. As an integrated company, we are uniquely positioned to offer you a wide range of career prospects and growth opportunities through the course of your career with us. We invite you to bring your ideas and help create sustainable solutions that improve quality of life and meet society’s evolving needs. 

Come be part of the Upstream and Global Operations Departments at Imperial which has more than 140 year history in Canada. Our offices are located across Canada.

What role you will play in our team


The Business Analyst Student will work as part of an integrated team within the Upstream Digital Accelerator, helping deliver digital innovation and solve operational challenges across our mining and in situ oil sands operations.
The student will collaborate with site operators, engineers, business stakeholders, data scientists, software developers, and management to understand business needs and translate them into practical digital solutions. Depending on the project, the student may help define requirements, map business processes, analyze data, develop business cases and project plans, coordinate activities, and design or prototype technology solutions.
Projects may involve artificial intelligence, data science, machine learning, mathematical optimization, analytics, robotics, automation, enterprise data platforms, and software development.
This role combines teamwork and stakeholder engagement with independent analysis and hands-on technical work. The ideal candidate is curious, collaborative, comfortable working through ambiguity, and interested in learning how technology can improve industrial operations.

What you will do

  • Work with business stakeholders, site personnel, engineers, and technical teams to understand operational challenges, user needs, and desired business outcomes.
  • Translate business needs into clear requirements, user stories, acceptance criteria, process maps, data requirements, and actionable work items.
  • Support the development of business cases, value assessments, project plans, delivery roadmaps, and implementation recommendations.
  • Help define project scope, objectives, assumptions, dependencies, risks, and success measures.
  • Collaborate with stakeholders and delivery teams to prioritize work based on business value, operational impact, technical feasibility, risk, and effort.
  • Collect, clean, analyze, and visualize operational and business data to identify trends, opportunities, root causes, and potential improvements.
  • Use analytics, business intelligence, statistical methods, and AI-enabled tools to support data-driven decisions.
  • Assist with the design, development, testing, and prototyping of analytics, automation, AI, optimization, or software solutions.
  • Develop and document process models, data models, analytical approaches, and solution workflows.
  • Evaluate and help integrate tools and technologies that improve workflows, productivity, decision-making, or operational performance.
  • Track work items, milestones, risks, issues, decisions, and dependencies, and provide clear progress updates.
  • Participate in solution testing, including validating requirements, analyzing results, documenting issues, and confirming that solutions meet user needs.
  • Help monitor the performance, reliability, adoption, and business value of delivered products or prototypes.
  • Create clear documentation, presentations, demonstrations, and training materials for technical and non-technical audiences.
  • Support meetings, workshops, interviews, demonstrations, and working sessions involving business and technical teams.
  • Follow company requirements for safety, cybersecurity, data governance, privacy, records management, and responsible AI.

About you

Skills and Qualifications

  • Currently enrolled in business analytics, computer science, data science, software engineering, engineering, mathematics, statistics, operations research, management information systems, or a related University program.
  • University student available for a work term beginning in January or May 2027
  • Currently enrolled in a university program and returning to full-time studies after the work term
  • To be considered for employment, your most recent unofficial transcript(s) must be submitted with your application
  • Able to gather business/stakeholder needs and turn them into clear requirements, user stories, process maps, or action plans.
  • Strong analytical, problem-solving, communication, and teamwork skills.
  • Experience with Python and SQL for data analysis, automation, development, or projects.
  • Basic understanding of: Statistics, Data visualization, Process/data modeling, Software requirements, Testing and quality assurance
  • Familiarity with project management and Agile practices (planning, prioritization, risk tracking, reporting).
  • Experience using development tools such as Git, GitHub, VS Code, or Jupyter Notebook.
  • Interest in AI, machine learning, analytics, optimization, automation, or software development.
  • Able to document and present technical information to both technical and non-technical audiences.
  • Curious, adaptable, organized, and comfortable learning new technologies.
  • Willing to travel occasionally and follow site safety requirements.

Preferred Qualifications/Experience 

  • Experience with cloud and enterprise data platforms such as Databricks, Snowflake, Microsoft Fabric, or Azure.
  • Experience with BI and visualization tools like Power BI or Tableau.
  • Knowledge of Generative AI, AI agents, prompt engineering, RAG, or responsible AI.
  • Experience with machine learning, forecasting, anomaly detection, predictive maintenance, or computer vision.
  • Knowledge of optimization, simulation, operations research, or mathematical modeling tools.
  • Experience with data engineering concepts such as data pipelines, APIs, data quality, governance, and metadata.
  • Familiarity with Agile tools and frameworks such as Azure DevOps, Scrum, or Kanban.
  • Experience with software testing, debugging, code reviews, and CI/CD practices.
  • Exposure to industrial sectors such as mining, energy, maintenance, reliability, process engineering, or operational technology data.

Work Location: Calgary, AB
 
 
Start Date: January or May 2027


Work term: 18 months


Other Considerations

  • For applicants selected to be interviewed, pre-employment background screening will be required
  • We thank all those who apply; however, only those candidates selected for interviews will be contacted
  • In certain situations, Imperial may use your application to consider your suitability for other positions in the company and may also provide the information to its affiliates, including affiliates of ExxonMobil Corporation, in connection with possible opportunities at those affiliates
  • To be considered for employment, your most recent unofficial transcript(s) must be submitted.
     


Application Deadline: September 30, 2026

Job Group Capability
Data Science, Digital & Analytics
Job Group
Computational & Data Sciences
Job Role Description
The AI Scientist Associate is responsible for developing solutions for well-defined AI problems with minimal supervision. Strong Python coding skills, familiarity with endorsed tools, and adherence to ExxonMobil AI best practices are required. Additionally, a solid understanding of AI fundamentals and hands-on experience in a specialized AI field are essential
Job Role Responsibilities
Conducts data acquisition, cleansing, exploratory data analysis (EDA), and feature engineering to gain insights from data for well‑defined AI problems
Trains physical, statistical, or machine‑learning models to meet defined metrics using endorsed Python libraries and other tools while following ExxonMobil AI best practices
Converts EDA outcomes and knowledge from business subject‑matter experts (SMEs) into model inputs (e.g. features)
Deploys solutions by collaborating with Machine Learning Engineers and supports sustainment activities
Documents throughout the lifecycle of the AI solution development process
Functional Skills
Applied Software Engineering for Data
Mathematical Framing of Business Problems
Deep & Reinforcement Learning
Machine Learning

Imperial is an Equal Opportunity Employer. Imperial is committed to providing equitable treatment and equal opportunity to all individuals and encourages all eligible applicants to apply.

Imperial conducts business in a manner that respects the land, environment, rights and cultures of Indigenous communities. In the areas where we explore, develop and operate, Imperial engages Indigenous communities in open and forthright consultation and strives to establish meaningful relationships built on mutual trust and respect. Please see here for more information on Imperial’s Indigenous Relations Guiding Principles and Guidelines.

Imperial is committed to supporting persons with disabilities throughout the recruitment process. We will work with qualified applicants to provide reasonable accommodation upon request at Recruit.Services.CA@exxonmobil.com.

Eligibility to work in Canada

All applicants who receive an offer of employment must be eligible to work in Canada on a regular full-time basis without restrictions on their start date.  Proof of eligibility shall be in the form of a Canadian birth certificate, Canadian passport, Canadian citizenship certificate, Canadian certificate of permanent residence, Canadian open work permit or receipt from Immigration Canada of an application for a post-graduate work permit. 

Proof of eligibility must be current and valid (not expired, cancelled or voided). Proof of eligibility will be required if an offer of employment is made. Failure to provide proof of eligibility at least six (6) weeks prior to the start date may result in the offer of employment being rescinded.

Job ID: 108615#LI-Onsite


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