Data Scientist
Government of Alberta•Edmonton, AB
•CA$82,168 - CA$107,710•Onsite
About The Position
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. 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. This role demands strong systems thinking, creative problem solving, experimentation, prototyping, results focus, and the agility to navigate evolving priorities and complex data challenges.
Requirements
- A university degree in a relevant discipline – such as Advanced Analytics, Data Science, Artificial Intelligence, Computer Science, or Statistics – is required, along with a minimum of four years of progressively responsible experience in related roles.
- Strong technical and analytical capabilities, sound judgment, and a proven ability to interpret complex data and translate it into actionable insights that support evidence based policy, program delivery, and operational decision making.
- Strong Python skills and associated libraries (pandas, NumPy, scikit-learn etc.) for data processing and modeling
- Solid foundation in statistics (hypothesis testing, regression, probability)
- Hands-on experience with core ML techniques (classification, regression, clustering, time series)
- Hands-on experience with SQL for data extraction and manipulations
- Fluency in developing strategic, decision-focused dashboards and reports
- Experience working with data visualization tools such as Matplotlib, Seaborn, Power BI, Tableau, or similar
- Hands-on experience in deploying or supporting production-grade machine learning models with a strong emphasis on model explainability, scalability, and operational integration
- Working knowledge of neural networks and deep learning fundamentals
- Hands-on exposure to NLP and text-based data
- Familiarity with LLM concepts such as embeddings, prompt design, and model APIs
- Experience working in cloud environment (AWS, Azure, or GCP)
- Ability to communicate analytical results clearly and concisely
- Strong commitment to continuous learning and staying current with emerging technologies, applying new approaches where appropriate to support organizational outcomes
- Experience contributing to analytics-related initiatives including project planning, cross-functional collaboration and solution delivery in a data-driven environment
- Knowledge of Alberta’s data privacy legislation (POPA), and related policies governing the ethical handling, protection, and sharing of sensitive or personally identifiable information in analytics workflows
Nice To Haves
- Experience with deep learning frameworks (PyTorch, TensorFlow)
- Familiarity with Spark or Databricks for large-scale data processing
- Exposure to deploying or supporting ML workloads in AWS and/or Azure (SageMaker, S3, Lambda, ECS/EKS, Azure ML, Blob Storage, Azure Functions etc.)
- Exposure to MLOps practices (MLflow, CI/CD for ML, model monitoring)
- Understanding of ETL vs ELT patterns and their application in analytics and reporting
- Understanding of cloud-based data platforms and data architectures such as lakehouse
- Formal certification from AWS or Azure
- Experience in data acquisition and integration from multiple sources.
- Proven ability to provide technical advice and analytical consultation to both technical teams and business stakeholders
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
Benefits
- Public Service Pension Plan (PSPP)
- Professional learning and development
- Positive workplace culture and work-life balance.
- Leadership and mentorship programs.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
