UDA Business Analyst - Students Seeking Opportunities 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. 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. We invite you to bring your ideas and help create sustainable solutions that improve quality of life and meet society’s evolving needs.

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.

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. 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 Able to gather business/stakeholder needs and turn them into transparent requirements, user stories, process maps, or action plans.

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). 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.

Willing to travel occasionally and follow site safety requirements.

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.

Experience with machine learning, forecasting, anomaly detection, predictive maintenance, or computer vision.

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.

Start Date: January or May 2027 Data Science, Digital & Analytics Computational & Data Sciences 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 is essential 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 Applied Software Engineering for Data Mathematical Framing of Business Problems 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. 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. Test Engineer, Cloud, Testing, Sustainability, Business Intelligence, Engineering, Technology, Energy #

📌 UDA Business Analyst - Students Seeking Opportunities (Calgary)
🏢 Exxon Mobil
📍 Calgary