Data Analytics & Data Science Consultant will work closely

Our client is looking for Data Analytics & Data Science Consultant will work closely with business stakeholders to develop analytics, data science, AI, and reporting solutions that support asset management, asset planning, reliability, and operational decision-making - 7296

6 months contract, likely will renew, Hybrid 3 days a week in Greater Vancouver

**Please note that for the successful candidate will be required to provide and use their own laptop for the duration of the contract.

Must Have:

• Strong Oracle SQL, Python, and Power BI skills.
• Experience with data engineering, analytics, data visualization, and data science.
• Knowledge of machine learning, statistical analysis, and AI/generative AI.
• Demonstrated experience working directly with business stakeholders and translating business needs into technical solutions.
• Strong analytical, problem-solving, communication, and presentation skills.
• Ability to independently take an ambiguous business problem from investigation through to a completed analytics solution.

Nice to Have:

• Experience in electric utilities, energy, infrastructure, engineering, or asset management is preferred. Knowledge of electrical systems, SAP EAM/S/4HANA, Microsoft Fabric, Power Automate, or Copilot would be considered an asset.
• The ideal candidate is someone who combines strong technical capabilities with business curiosity—someone interested in understanding how the business and electric utility systems work, rather than focusing solely on technology.

Responsibilities

• This is a business-facing technical role requiring someone who can understand business problems, work directly with complex data, develop solutions, and communicate meaningful insights to stakeholders.
• Work directly with business stakeholders to understand business processes, challenges, and analytics needs.
• Translate business problems into practical data, analytics, AI, and automation solutions.
• Extract, transform, integrate, and analyze large datasets from multiple enterprise systems.
• Develop complex Oracle SQL queries and use Python for data processing, automation, advanced analytics, and data science.
• Design and develop Power BI dashboards, data models, KPIs, and visualizations that provide actionable business insights.
• Perform exploratory and statistical analysis to identify trends, risks, anomalies, and drivers of asset and business performance.
• Develop predictive analytics and machine-learning solutions where appropriate.
• Identify and prototype practical AI and generative AI use cases, including AI agents and intelligent workflows.
• Investigate data quality issues and work with business and Technology teams to improve data reliability.
• Present analytical findings and recommendations clearly to both technical and non-technical stakeholders.
• Develop an understanding of electric utility assets, maintenance, reliability, asset health, and asset management processes.
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