Senior Business Intelligence Advisor to deliver advanced analytics and data solutions supporting Oil & Gas initiatives Job Toronto area

Our energy client is seeking a Senior Business Intelligence Advisor to deliver advanced analytics and data solutions supporting Oil & Gas initiatives

Join a leading energy organization focused on advancing data-driven decision-making across large-scale operations. This role leads analytical projects from design to delivery, applying statistical modelling, data validation, and forecasting using SQL, Python, R, and Microsoft Azure Databricks. The position offers visibility across business units, influencing performance optimization and continuous improvement through actionable insights. Candidates will collaborate with cross-functional teams in a hybrid environment based in North York, ON.

Contract, North York, 3 days a week onsite

Hybrid Model:
In-Office (Monday, Tuesday & Thursday), Remote (Wednesday & Friday); drivers abstract required due to some travel required (approximately 5% of time)

9 months

Must Haves

7+ years in Business Intelligence
, data analytics
, and statistical analysis supporting business decision-making

Advanced proficiency in SQL
, Python
, and R for large and complex data sets

Experience with Microsoft Azure Databricks and modern analytics platforms

Strong command of Excel
, Power BI
, Visio
, and GIS

Degree in Mathematics, Economics, Computer Science, Information Technology, Statistics, or a related field

Nice to Have

Experience with predictive modelling, forecasting, and statistical analysis

Knowledge of machine learning techniques and their business applications

Experience in data warehousing, data modelling, and modern analytics environments

Familiarity with cloud-based analytics and scalable data solutions

Responsibilities

Partner with internal teams to identify strategic business needs and analytics opportunities

Lead end-to-end analytical initiatives from problem definition to results validation

Deliver analytics reports and insights aligned with stakeholder priorities

Develop and validate statistical regression and prediction models using complex data sets

Oversee data quality assessments and recommend collection and reporting improvements

Guide the creation and enhancement of dashboards and reporting solutions for leadership

Lead cross-functional workshops to identify innovative applications for data analytics