Business Data & AI Specialist – GTM Data & Systems Strategy

Manpower is partnering with a leading organization in the energy sector to recruit a Business Data & AI Specialist – GTM Data & Systems Strategy Location: Calgary, AB Duration: 1 year contract Work Model: Hybrid Role Summary: GTM D&SS is seeking a Business Data & AI Specialist to work within the Gas Transmission business and deliver applied data science, AI/ML, and automation solutions that directly support operational priorities including reliability, compliance, asset management, and decision support. The role will be embedded within D&SS and will partner closely with operations, engineering, integrity, records, asset management teams, etc. to understand their challenges, define requirements, and translate them into practical, data-driven solutions. The role requires strong technical execution skills with a focus on understanding the business context, delivering measurable outcomes, and ensuring solutions are usable, auditable, and aligned with how the business operates. This role leverages technology platforms to build and deliver business-owned solutions that address GTM-specific needs. Key Responsibilities Partner with business stakeholders across operations, engineering, reliability, records, and asset management to identify, scope, and prioritize data and AI opportunities. Translate business questions and operational pain points into well-defined analytical or modeling problems. Ensure solutions are grounded in business context, regulatory requirements, and operational realities. Perform data acquisition, cleansing, transformation, and validation across structured and unstructured datasets. Conduct exploratory analysis to surface trends, anomalies, risks, and improvement opportunities relevant to GTM operations. Design, build, test, and tune machine learning models using established techniques (e.g., classification, regression, clustering, natural language processing) to address specific business use cases. Build Generative AI and Agentic AI‑based solutions, including prompt engineering and workflow automation. Deliver reproducible analyses and clearly communicate findings, recommendations, and limitations to both technical and non-technical audiences. Create business-facing visualizations and dashboards that support day-to-day decision-making. Prepare and maintain documentation that supports knowledge transfer, auditability, and operational continuity. Apply appropriate evaluation methodologies and document assumptions, limitations, and model performance. Write clean, well-structured Python code that meets quality and security standards, working within shared repositories (Git). Support model deployment and operationalization, including basic MLOps practices such as monitoring inputs, outputs, and performance over time. Collaborate with D&SS, TIS, business partners, and domain experts to ensure solutions meet operational needs. Identify opportunities to enhance or extend existing business solutions within the assigned domain. Stay current on practical advances in data science, ML, and AI that are relevant to the business context. Required Qualifications Bachelor’s degree in data science, Computer Science, Engineering, Statistics, Mathematics, or a related field. 6-8 years of combined experience applying data, analytics, and AI/ML to business or operational problems, with demonstrated ability to translate business needs into practical, data-driven solutions in the energy industry. Strong proficiency in Python and common data science libraries. Solid understanding of applied machine learning concepts and applied statistics. Demonstrated ability to communicate insights and recommendations to business stakeholders clearly and concisely. Experience working collaboratively across functions, not just within a technical team. Ability to work independently within a defined scope and effectively collaborate across teams. Preferred Qualifications Experience with Generative AI, large language models (LLMs), or agent‑based workflows or agent-based workflows in applied business settings. SQL proficiency and experience working with operational or analytical databases. Experience building business-facing dashboards or reports (e.g., Power BI). Familiarity with cloud-based platforms (Azure preferred; AWS or GCP acceptable). Experience working in engineering, operations, regulated, or energy sector environments. Exposure to documentation-heavy or audit-sensitive work contexts.

The specialist will deliver applied data science, AI/ML, and automation solutions to support operational priorities like reliability and asset management. They will partner with cross-functional teams to translate business pain points into data-driven, auditable, and practical technical solutions.

Candidates must hold a bachelor's degree in a technical field and possess 6-8 years of experience applying data and AI/ML to operational problems. Proficiency in Python and strong communication skills are essential for translating complex technical insights to non-technical stakeholders.

• Visualisation de donnéesSouhaitée
• Power BISouhaitée
• SQLSouhaitée
• Analyse de donnéesSouhaitée
• Apprentissage automatiqueSouhaitée
• GitSouhaitée
• PythonSouhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• Data Science
• Machine Learning
• Artificial Intelligence
• Automation
• Data Analysis
• SQL
• Power BI
• Generative AI
• Prompt Engineering
• MLOps
• Statistics
• Data Visualization
• Git
• Cloud Platforms

• Data & Analytics
• Energy
• Technology
• Software
• Engineering

Formation minimale

Baccalauréat

Expérience minimale

5+ ans

Postuler avant le

3 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte