Senior Machine Learning Specialist

Senior Machine Learning Specialist

Data Scientist / AI Developer

Client: Government of Alberta – Technology & Innovation

Project: Data Projects / Data Centre of Excellence

Location: Edmonton, Alberta

Work Arrangement: Remote within Canada; onsite meetings may be required

Hours: 36.25 hours/week

Contract Extension: Up to 6 months

Position Overview

The Government of Alberta's Data Centre of Excellence is seeking an experienced Machine Learning Specialist to support the design and development of analytical data products and services that advance the Government of Alberta Data Strategy.

The successful candidate will work as a technical expert within a cross-functional team, applying machine learning, artificial intelligence, data science, statistical analysis, data modelling, and advanced analytics to support government initiatives and improve services for Albertans.

This position may involve a combination of machine learning model development, AI development, data analysis, data science, data engineering, data modelling, statistical analysis, technical analysis, business analysis, and data product design and delivery.

Key Responsibilities

• Provide hands-on technical leadership, advice, and direction for strategic data initiatives.
  

• Work with internal and external stakeholders to understand analytical needs and determine how data can best support business and policy objectives.
  

• Identify appropriate opportunities for applying AI and Machine Learning to complex public-sector challenges.
  

• Develop, train, evaluate, and implement machine learning models using appropriate tools and techniques.
  

• Create data collection, normalization, cleansing, and preparation processes.
  

• Prepare data for prescriptive and predictive modelling .
  

• Perform machine-learning-driven analysis of large datasets and communicate findings through reports and analytical products.
  

• Develop analytical models, reports, dashboards, visualizations, and insights to support government services and policymaking.
  

• Integrate trained ML models into applications and analytical solutions.
  

• Apply statistical classification and data-mining techniques, including methods such as clustering, partition trees, and logistic regression.
  

• Develop and share analytical models and data products.
  

• Support the development of full-stack data analytics and AI applications where required.
  

• Conduct complex data analysis and collaborate with data engineers and analysts across projects.
  

• Gather and document business and technical requirements.
  

• Capture business and technical metadata for machine learning products.
  

• Develop auditing, accountability, and transparency mechanisms for ML capabilities.
  

• Work within privacy legislation and provide ethical and practical guidance related to ML implementation.
  

• Identify and escalate project issues and risks as appropriate.
  

• Facilitate, coach, and mentor others in the application of ML.
  

• Help identify and select appropriate ML tools, services, and infrastructure.
  

• Work effectively in a multi-vendor and cross-functional environment.
  

• Perform other related responsibilities as required.
  

Requirements

Mandatory Qualifications

Education

• Bachelor's degree in Computer Science or a related field . Equivalencies will be considered.
  

Experience

Candidates must demonstrate:

• 6+ years of experience using statistical and computer languages such as R, Python, and SQL .
  

• 6+ years of experience building analytical and quantitative analysis models.
  

• 6+ years of experience preparing data for prescriptive and predictive modelling .
  

• 6+ years of experience with data analytics and data science approaches and methods, including complex statistical modelling.
  

• 6+ years of experience applying Artificial Intelligence (AI) or Machine Learning (ML) to data science or analytics, including ML for anomaly detection, predictive monitoring, or AI-assisted data transformation and automation.
  

Nice-to-Have Qualifications

• 5+ years of experience with data sharing, data linkage, de-identification, metadata, data quality, ethics, synthetic data, and data literacy.
  

• 5+ years of experience combining raw data from multiple sources and domains.
  

• 5+ years of experience understanding complex business questions and framing appropriate analytical questions.
  

• 5+ years of experience preparing visualizations, dashboards, and analytical models.
  

• 6+ years of experience with statistical and data-mining techniques.
  

• 4+ years of experience working with large government datasets.
  

Work Schedule & Location

• 36.25 hours per week
  

• Standard hours: 8:15 AM – 4:30 PM Alberta Time, Monday to Friday
  

• Work must be performed from within Canada .
  

• The position is anticipated to be 100% remote .
  

• The resource must be available for onsite meetings when required.
  

• Onsite meetings may occur approximately 3–4 times per fiscal year in Edmonton.
  

• The Government of Alberta does not cover travel, relocation, commuting, accommodation, or related expenses for onsite meetings.
  

Deliverables & Reporting

• Specific project deliverables and due dates will be established by the client team in conjunction with project management.
  

• Weekly and monthly status reporting will be required.
  

Submission Requirements

Candidates submitted for this position must provide:

• Updated resume.
  

• All required experience must be clearly described under the specific job/project where the experience was obtained.
  

• Each job/project must include employment/project dates in MMM/YYYY – MMM/YYYY format.
  

• Three professional references who can speak to similar work, with the most recent reference listed first.
  

Background & Training Requirements

• Standard criminal record/background check may be required before commencement.
  

• Successful candidates must complete mandatory Government of Alberta training, including Freedom of Information and Protection of Privacy Act (FOIP) and security awareness training.
  

Selection Process

Scoring Methodology:

• Financial/Pricing: 20%
  

• Resource Qualifications: 20%
  

• Interview: 60%
  

Interviews are expected to take place approximately two weeks after the posting closes .

This is an excellent opportunity for experienced Data Scientists, Machine Learning Specialists, AI Developers, and Applied AI professionals with strong Python/SQL/R, statistical modelling, predictive analytics, and production ML experience.