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GOAPRDJP00000988 - Machine Learning Specialist

Full-time

S M Software Solutions Inc

Machine Learning Specialist – GOAPRDJP00000988

Job Overview

The Government of Alberta (GoA) is seeking a Machine Learning Specialist to support strategic data initiatives within the Data and Content Management Division and the Data Centre of Excellence .

The successful candidate will provide hands-on expertise in machine learning, artificial intelligence, data science, statistical analysis, data modelling, data engineering, and analytical product development . This role will help government teams leverage data assets to develop evidence-based insights, improve public services, support policy decisions, and advance the implementation of the GoA Data Strategy.

The Machine Learning Specialist will work with cross-functional teams and internal/external stakeholders to identify appropriate opportunities for ML and AI, develop analytical models and products, prepare complex datasets, integrate ML capabilities into applications, and provide guidance on privacy, ethics, transparency, and responsible use of AI.

Role Snapshot

Position Details Information Job Title

GOAPRDJP00000988 – Machine Learning Specialist

Client

Government of Alberta

Work Location

7000 – 113 ST, Edmonton, Alberta, Canada, T6H 5T6

Work Arrangement Remote Estimated Start Date

January 9, 2026

Estimated End Date

August 31, 2027

Business Days

Estimated Hours/Day

7.25

Maximum Extension

6 Months

Application Deadline

Tuesday, August 18, 2026 at 4:00 PM EST

Key Responsibilities

  • Machine Learning & AI Development
  • Develop and apply machine learning and artificial intelligence solutions to complex government and public-sector challenges.
  • Identify appropriate opportunities for applying ML and determine when ML is not suitable.
  • Identify prerequisites and data requirements for successful ML applications.
  • Develop training scripts and train models using appropriate ML packages and frameworks.
  • Build analytical models and algorithms that deliver measurable business value.
  • Run ML-driven analysis of large datasets and communicate findings to stakeholders.
  • Integrate trained ML models into applications and analytical products.
  • Support the development of full-stack data analytics and AI applications as required.
  • Identify and select appropriate ML tools, services, and infrastructure.
  • Data Science & Statistical Analysis
  • Analyze and organize raw data to prepare it for predictive and prescriptive modelling.
  • Apply statistical and data mining techniques to address complex business and policy questions.
  • Develop analytical and quantitative models to generate actionable insights.
  • Apply statistical classification and modelling techniques, including:
    • K-means clustering
    • Hierarchical clustering
    • Partition trees
    • Logistic regression
  • Conduct complex data analysis across large and diverse datasets.
  • Develop and share analytical models, reports, insights, and data products.
  • Use Python, R, and SQL for data analysis, modelling, and statistical programming.
  • Data Preparation & Engineering
  • Create procedures for data collection, normalization, cleansing, and preparation.
  • Combine and analyze raw data from multiple sources and across different domains.
  • Prepare high-quality datasets for predictive and prescriptive modelling.
  • Support data engineering and data modelling activities as required.
  • Capture and document business and technical metadata for ML products.
  • Support data quality and data preparation activities throughout the analytics lifecycle.
  • Analytics Products, Visualization & Insights
  • Develop ML analytics, reports, dashboards, and insights to support improved government services and policymaking.
  • Prepare visualizations and analytical products that communicate complex findings effectively.
  • Translate complex analytical results into actionable recommendations for technical and non-technical stakeholders.
  • Develop evidence-based analytical products that support the GoA Data Strategy.
  • Design and deliver data products that can be shared across ministries and with external stakeholders.
  • Responsible AI, Privacy & Governance
  • Develop auditing, accountability, and transparency mechanisms for ML capabilities.
  • Ensure ML and AI solutions are designed and implemented within applicable privacy legislation.
  • Provide ethical and practical guidance on ML implementation.
  • Consider privacy, security, data quality, ethics, transparency, and accountability throughout the ML lifecycle.
  • Support data de-identification and synthetic data initiatives.
  • Apply appropriate approaches to data sharing, data linkage, metadata, data quality, and responsible use of government data.
  • Stakeholder Engagement & Strategic Advisory
  • Provide hands-on support, leadership, advice, and direction for strategic data initiatives.
  • Collaborate with internal and external clients to understand analytical requirements and determine how data can best address their needs.
  • Gather, clarify, and document client business and technical requirements.
  • Frame complex business questions into appropriate analytical questions and identify effective approaches to solve them.
  • Facilitate, coach, and mentor teams in applying ML to complex public-sector challenges.
  • Provide expertise and leadership in the design and execution of analytical projects.
  • Work collaboratively with data engineers, analysts, technical specialists, and multidisciplinary project teams.
  • Project Delivery & Collaboration
  • Work within cross-functional and multi-vendor/staff environments.
  • Collaborate with the Manager, Analytics Capability Centre, and other stakeholders.
  • Deliver analytical and ML services iteratively as business needs and technical opportunities evolve.
  • Identify, communicate, and escalate project issues and risks as appropriate.
  • Contribute to strategic data initiatives supporting the implementation of the Government of Alberta Data Strategy.
  • Perform other related responsibilities as required.

Required Skills & Experience – Must Have

  • Comprehensive experience using statistical and programming languages, including:
    • Python
    • R
    • SQL
  • Experience building analytical and quantitative models.
  • Experience preparing and organizing data for predictive and prescriptive modelling.
  • Strong understanding of different approaches and methods for data analytics and data science, including complex statistical modelling.
  • Experience applying Artificial Intelligence (AI) and Machine Learning (ML) to data science and analytics.
  • Experience using ML/AI for applications such as:
    • Anomaly detection
    • Predictive monitoring
    • AI-assisted data transformation
    • Data engineering automation
  • Experience conducting complex data analysis and developing analytical models.
  • Ability to translate business requirements into analytical solutions and actionable insights.

Nice-to-Have Skills

  • Experience and knowledge of:
    • Data sharing
    • Data linkage
    • Data de-identification
    • Metadata
    • Data quality
    • Data ethics
    • Synthetic data
    • Data literacy
  • Experience combining raw data from a variety of sources and across multiple domains.
  • Experience understanding complex business questions and framing the right analytical questions to solve business problems.
  • Experience developing visualizations, dashboards, reports, and analytical models.
  • Strong knowledge of statistical and data mining techniques.
  • Experience working with large government datasets.
  • Experience supporting public-sector data and analytics initiatives.
  • Experience with responsible AI, model transparency, auditability, and accountability.
  • Experience mentoring or coaching teams in machine learning and data science practices.

Project & Business Context

The Data and Content Management Division follows a one-government approach to information and privacy governance, decision-making, and service delivery across the Government of Alberta. The division aims to enhance data access and collaboration, reduce data duplication, promote innovation, and ensure effective and efficient government services.

The Data Centre of Excellence requires a Machine Learning Specialist to support the design and development of analytical data products and services that enable the Government of Alberta to better leverage its data assets and implement its Data Strategy.

The successful candidate will play a key role in applying advanced analytics, machine learning, data modelling, de-identification, synthetic data creation, visualization, and evidence-based approaches across government ministries and external stakeholder environments.

This is a multifaceted role that may include responsibilities across:

  • Machine learning model development
  • Artificial intelligence
  • Data science
  • Data analysis
  • AI development
  • Data engineering
  • Data modelling
  • Statistical analysis
  • Data strategy and advisory
  • Data product design and delivery
  • Data architecture
  • Technical analysis
  • Business analysis

Work Arrangement

Remote: The resource will work remotely but must be available to attend onsite meetings in Edmonton when required .

How to Apply

If you have the required experience and are available for new opportunities, please submit the following documents to ***email_hidden*** by Tuesday, August 18, 2026 at 4:00 PM EST :

  • Updated Resume in Word format – Mandatory
  • Skills Matrix and References – Mandatory
  • Expected Hourly Rate – Mandatory
  • Visa Status – Mandatory
  • LinkedIn ID – Mandatory

Please note: Applications without the mandatory documents cannot be processed or submitted.

Apply Online

For daily job updates, you can also join our WhatsApp group.

If this opportunity is not a match for your profile, please share it with qualified Machine Learning Specialists, Data Scientists, or ML/AI Professionals with strong experience in Python, R, SQL, statistical modelling, predictive/prescriptive analytics, machine learning, AI, data preparation, and government or public-sector data initiatives.

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