Data Scientist

Job Information

• Job Title: Data Scientist
• Job Requisition ID: 89382
• Ministry: Treasury Board & Finance
• Location: Edmonton
• Full or Part-Time: Full Time
• Hours of Work: 36.25
• Permanent/Temporary/Wage: Permanent
• Scope: Open Competition
• Closing Date: November 17, 2026
• Classification: Program Services 4
• Salary: $3,148.20 to $4,126.82 bi-weekly ($82,168 - $107,710/year)

Tax and Revenue Administration (TRA), Treasury Board and Finance (TBF) is responsible for the collection of revenue and the administration of Alberta’s tax, revenue and related benefit programs. The focus of our organization is to ensure a fair, efficient and effective provincial tax and revenue system. To learn more about Tax and Revenue Administration and what it has to offer, follow this link: Tax and levy payments and administration .

Role Responsibilities

Are you an experienced data scientist, advanced analyst or business intelligence & analytics professional who thrives at the intersection of data, technology, and strategic decision-making? We are seeking a results-oriented Data Scientist to join our high-performing data science team within Tax and Revenue Administration (TRA). This role plays a critical part in enabling data-driven decisions through both advanced reporting and applied machine learning.

As a Data Scientist reporting to the Manager, Business Intelligence & Analytics, you will be responsible for delivering high-impact analytics and machine learning solutions that directly inform decisions, strategies, and program effectiveness.

Key Responsibilities

• Analyze large, complex structured and unstructured datasets to identify trends, patterns, and actionable insights
• Perform exploratory data analysis (EDA) and feature engineering to support modeling efforts
• Design and implement data cleaning, transformation and processing logic for analytical and ML use cases
• Develop, validate, and maintain statistical, machine learning and neural network models to solve business problems
• Develop NLP solutions such as text classification, information extraction, summarization, and document similarity
• Apply pre-trained LLMs using techniques such as prompt engineering, embeddings, and retrieval-augmented generation (RAG)
• Collaborate with data engineers, analysts and other stakeholders to design and support scalable data and ML pipelines
• Support model deployment and performance evaluation on AWS, Azure or other cloud and hybrid environments for operation
• Monitor model performance, data quality, data drifts, and pipeline reliability
• Create reports, develop dashboards aligned with TRA’s strategic goals and communicate findings, assumptions, and results clearly to technical and non-technical stakeholders
• Ensure data quality, reproducibility, and documentation of analytical work
• Promote data culture through trainings and consultative support and apply best practices for data governance, privacy, security, and ethical use of data and responsible AI
• Ensure compliance with Alberta’s data privacy legislation, including Protection of Privacy Act (POPA), and support TRA’s standards for ethical data use, protection, and transparency

APS Competencies

• Systems Thinking – Work within the APS takes place in a broader, integrated, and inter‑related environment. Actions in one area may impact multiple groups and initiatives both within and outside the APS. Applying systems thinking helps ensure these broader impacts and interdependencies are considered.
• Creative Problem Solving – Demonstrates the ability to assess options and their implications in new ways, enabling the development of effective and sustainable outcomes and solutions.
• Agility – Demonstrates the ability to anticipate and assess change, adapt to shifting priorities, maintain resilience under uncertainty, and work effectively in evolving environments.
• Drive for Results – Demonstrates the ability to set and accomplish priorities that support outcomes aligned with government direction, departmental objectives, and public expectations.

This link will assist you with understanding competencies.

Qualifications

University degree in a relevant discipline – such as Advanced Analytics, Data Science, Artificial Intelligence, Computer Science, or Statistics – plus four years of progressively responsible experience in related roles.

Equivalency

• 1 year of education for 1 year of experience; or
• 1 year of experience for 1 year of education.

Preference will be given to those with a university degree in a relevant discipline.

The successful candidate will demonstrate strong technical and analytical capabilities, sound ju