Business Data and AI Specialist

Are you a data scientist who thrives on solving real-world operational challenges rather than just building models in a vacuum? Our client is integrating advanced analytics directly into the heart of their operations. We are looking for a Business Data & AI Specialist to be a strong part of their Data & Smart Solutions (D&SS) team. In this high-impact role, you will bridge the gap between complex data technologies including Machine Learning, Generative AI, and Agentic AI workflows and core operational functions like asset management, engineering, compliance, and reliability. If you are passionate about writing clean code, building usable solutions, and driving measurable, audit-ready outcomes in the energy sector, this is your opportunity to shape the future of their digital infrastructure

Advantages
Direct Operational Impact: Your work won't sit on a shelf. You will build business-owned tools, dashboards, and AI agents that directly influence day-to-day decision-making and asset reliability.

Cutting-Edge Tech in an Essential Industry: Deploy modern ML, NLP, Generative AI, and workflow automation within a heavily regulated, critical infrastructure environment.

Collaborative & Embedded Culture: Work closely alongside engineering, records, and integrity domain experts who rely on your technical expertise to solve their toughest operational pain points.

Focus on Practical Innovation: They value reliable, reproducible, and scalable delivery over purely theoretical experimentation.

Professional Growth: Work in an environment that encourages staying current with advances in AI, cloud platforms, and modern MLOps practices.

Responsibilities
Business Partnership & Scoping: Collaborate directly with cross-functional stakeholders (Operations, Engineering, Integrity, Records) to translate complex business questions and operational challenges into actionable data science and modeling projects.

Data Engineering & Analysis: Acquire, clean, transform, and validate structured and unstructured operational datasets. Perform exploratory data analysis to surface anomalies, operational risks, and efficiency opportunities.

Model & AI Solution Development: Design, tune, and test ML models (classification, regression, clustering, NLP) alongside modern Generative AI and Agentic AI workflows with robust prompt engineering.

Visualization & Decision Support: Build intuitive, business-facing dashboards and visualizations (e.g., Power BI) that empower non-technical teams to make data-driven decisions.

Code & MLOps Excellence: Write clean, modular Python code using Git. Support end-to-end model deployment, monitoring, and basic MLOps to maintain model performance and auditability over time.

Documentation & Communication: Clearly translate technical findings to diverse audiences, maintaining thorough documentation for knowledge transfer, regulatory compliance, and audit readiness.

Qualifications
Education: Bachelor’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.

Experience: 6–8 years of combined experience applying data, analytics, and AI/ML to solve business or operational challenges, specifically within the energy industry.

Technical Proficiency: Strong expertise in Python and its standard data science stack (e.g., Pandas, NumPy, Scikit-learn).

Core Concepts: Solid grasp of applied machine learning, statistical modeling, and basic MLOps practices.

Collaboration & Communication: Proven track record of translating business needs into data solutions and communicating insights clearly to both technical and non-technical stakeholders.

Practical experience applying Generative AI, Large Language Models (LLMs), or agent-based workflows to business processes.

Strong SQL skills and hands-on experience querying operational or analytical databases.

Proficiency with cloud environments (Azure preferred; AWS or GCP acceptable).

Hands-on experience building interactive dashboards using Power BI.

Prior experience working in regulated, engineering-heavy, or documentation-intensive environments.

Scope & Work Style Expectations

Autonomous Execution: Work independently on routine and moderately complex projects within defined operational scopes while knowing when to escalate cross-functional risks.

Business-Centric Focus: Prioritize consistent operational value, reliability, and solution usability over purely exploratory research.

Contextual Depth: Build a deep understanding of the operational and regulatory context behind the data you analyze

Summary
This is an excellent chance to grow your career as a technical expert within a leading energy organization. Our client values innovation and provides a space where your technical contributions directly impact the success of their commodity marketing and risk management operations. If you are passionate about the work you do and enjoy the challenge of complex systems and wants to be part of a forward-thinking team, we want to hear from you. Please apply directly to this job ad or reach out to your Randstad Digital representative immediately!

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Good luck!

Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

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