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Added 5 mins ago
IG
Model Risk Management Specialist
Infotree Global Solutions
Montreal, QC
- Contract
Job Title: Model Risk Management Specialist ( Finance Project Manager)
Added 5 mins ago
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Director, Financial Crime
Deloitte
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- Full-time
Job Type: PermanentWork Model: HybridReference code: 135527Primary Location: Vancouver, BCAll Available Locations: Vancouver, BC; Toronto, ON
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Deloitte
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- Full-time
Job Type: PermanentWork Model: HybridReference code: 135246Primary Location: Vancouver, BCAll Available Locations: Vancouver, BC
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Added 37 mins ago
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Added 37 mins ago
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Added 1 hour ago
CB
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Added 1 hour ago
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Cape Breton Job Board
Sydney Indian Reserve No. 28A, NS · Sydney, NS
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Click HERE to view the job description, qualifications and to apply.
Added 1 hour ago
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Added 1 hour ago
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Added 1 hour ago
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Alberta iGaming Corporation (AiGC)

Lead Data Scientist

AB, Canada
Greater Edmonton Metropolitan Area, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Apr 5, 2027
Experience: 7+ years of progressively responsible experience in data science, advanced analytics, business intelligence, or quantitative analysis.
Posting language: English
Posted: Oct 7, 2026

Original job description

About the Job

The Alberta iGaming Corporation (AiGC) is a provincial Crown corporation established to conduct and manage online gaming in Alberta. Alberta's regulated iGaming market launched in July 2026, creating a unique opportunity to help shape a new industry in the province. AiGC works with some of the world's largest gaming operators and is building the legal, regulatory, and operational frameworks that support a modern, competitive, and responsible online gaming market.

We're looking for a Lead Data Scientist to lead the application of advanced data science and analytical methodologies to enable safe, fair, and responsible iGaming in Alberta by providing actionable insights, strengthening AiGC oversight, detecting and mitigating risks, and supporting evidence-based decision-making while prioritizing market integrity, transparency, and sustainability of Alberta's regulated online gaming environment.

Why Join AiGC?

AiGC is building a modern, regulated conduct and manage crown agency from the ground up. This is a rare opportunity to step into an organization at the earliest stage and shape how our operation comes together.

Who You Are

You are a highly skilled data science professional with a strong blend of technical expertise, strategic thinking, and business acumen. You have a proven ability to transform complex data into meaningful insights, develop advanced analytical solutions, and influence decision-making at all levels of an organization. You are collaborative, curious, and results-oriented, with a passion for data quality, continuous improvement, and solving complex business challenges. You thrive in dynamic environments, communicate complex concepts with clarity, and are committed to leveraging data and analytics to create measurable value and support organizational objectives.

About the Role

In this role you will own:

Data Quality Management

Manage and monitor operators reporting compliance with AiGC's data dictionary and data standards in partnership with the Data Platforms team.

Drive consistency and standardization of data reporting across multiple operator platforms and technology environments.

Develop and monitor data quality metrics to identify data issues, reporting discrepancies, compliance gaps, and emerging risks, and develop actionable mitigation strategies

Enhance data-driven market insights

Develop, maintain, and continuously enhance operational performance dashboards to monitor key metrics, assess market growth, player behaviour, operator performance, and emerging industry trends.

Produce market intelligence reports, trend analyses, and data-driven insights

Design and implement risk indicators, predictive models, and early warning systems to proactively monitor operator activity, compliance risks, market anomalies, and emerging threats.

Translate complex analytical findings into clear, concise, and actionable intelligence for technical and non-technical audiences.

Data Strategy and Advanced Analytics

Support the development of an enterprise iGaming analytics roadmap, ensuring alignment with organizational priorities, requirements, and strategic objectives.

Design and implement predictive models to support revenue forecasting, player behaviour analysis, market growth projections, and risk identification.

Lead advanced statistical analyses, predictive analytics initiatives, and evaluation frameworks to evaluate key performance metrics.

Develop and enhance business intelligence solutions, dashboards, and interactive visualizations that provide timely and actionable insights to executives and stakeholders.

Strategic Decision-Making Support

Support the development of high-quality briefing materials, reports, presentations, and strategic insights for executives, senior leadership, and the Board to support decision-making and policy development.

Conduct impact assessments to evaluate the potential effects of regulatory, legislative, market, technology, and competitive changes on Alberta's iGaming market.

Lead scenario modeling, forecasting, and predictive analyses to inform strategic planning, risk management, revenue projections, and market development initiatives.

Provide evidence-based insights on market performance, player behaviour, operator performance, and emerging risks.

Monitor and assess industry trends, regulatory developments, and market dynamics to identify opportunities, challenges, and strategic implications.

Organizational Leadership & Capability Building

Support the establishment of enterprise-wide analytical standards, methodologies, and best practices to ensure consistency, quality, transparency, and reliability of analytical outputs.

Support the growth of a strong data-driven culture by strengthening organizational data literacy, promoting the effective use of data and analytics, and embedding evidence-based decision-making across strategic, regulatory, and operational functions.

Lead cross-functional analytics initiatives including development and delivery of corporate KPIs that support organizational priorities, AiGC oversight, market performance, player protection, responsible gambling, and operational excellence.

Foster collaboration and partnership among Operations, Finance, Responsible Gambling, Anti-Money Laundering (AML), Privacy, and Technology teams to maximize the value of data and analytics across the organization.

What You Bring

Education

Post-secondary degree or diploma in a quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Economics, Engineering), or an equivalent combination of education and experience.

Master's degree in a related field is preferred.

Relevant certifications are an asset, such as Databricks (Machine Learning or Data Science), Microsoft Power BI or Azure, or Accredited Professional Statistician (P.Stat.).

Experience

7+ years of progressively responsible experience in data science, advanced analytics, business intelligence, or quantitative analysis.

Experience developing predictive models, statistical analyses, machine learning solutions, and forecasting methodologies.

Experience working with large, complex, and diverse datasets in highly regulated environments.

Experience presenting analytical insights and recommendations to senior leadership; experience presenting to Boards is an asset.

Experience in cross-functional initiatives and influencing decision-making through data-driven insights.

Experience establishing data quality standards and performance measurement frameworks.

Experience with iGaming, gaming, financial services, digital platforms, regulatory environments, risk management, and fraud analytics are considered assets.

Technical Knowledge

Advanced proficiency in SQL and Python; R is an asset.

Hands-on experience with Spark/PySpark in Azure Databricks, working within a governed lakehouse environment (Unity Catalog, Delta Lake).

Experience building dashboards and semantic models in Power BI.

Experience analyzing financial and market data, such as gross gaming revenue components, gaming activity and player activity.

Advanced knowledge of statistical and machine learning methods, including time-series forecasting, anomaly detection, behavioural segmentation, and causal or quasi-experimental methods for evaluating the impact of policy and market changes.

Strong model lifecycle practices, including version control (Git), experiment tracking (e.g., MLflow), documentation, and model explainability.

Experience analyzing sensitive, individual-level data in line with privacy obligations, including de-identification and data minimization is an asset.

Apply About employer

More about this job

Responsibilities

Lead data quality oversight, market intelligence, dashboards, predictive models, and risk indicators to support responsible iGaming regulation and market integrity. Provide evidence-based analysis and strategic decision support while establishing analytical standards and building data literacy across AiGC.

Requirements

Requires a post-secondary qualification in a quantitative discipline or equivalent experience, with a master's degree preferred, and at least seven years of relevant experience. Candidates should have advanced SQL and Python skills, experience with Databricks, PySpark, Power BI, predictive analytics, and regulated or complex datasets, as well as the ability to communicate insights to senior leaders.

Skills

Data Science
Advanced Analytics
SQL
Python
PySpark
Azure Databricks
Power BI
Predictive Modeling
Machine Learning
Statistical Analysis
Time-Series Forecasting
Anomaly Detection
Data Quality Management
Risk Analysis
Data Visualization
Stakeholder Communication

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Advanced Analytics
SQL
Python
R
Spark
PySpark
Azure Databricks
Unity Catalog
Delta Lake
Power BI
Machine Learning
Predictive Modeling
Statistical Analysis
Time-Series Forecasting
Anomaly Detection
Behavioral Segmentation
Causal Analysis
Quasi-Experimental Methods
Revenue Forecasting
Data Quality
Data Governance
Lakehouse
Git
MLflow
Model Explainability
Responsible Gambling
Anti-Money Laundering
Risk Management
iGaming

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