Candidates must demonstrate:

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 elevate 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

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

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 robust Python/SQL/R, statistical modelling, predictive analytics, and production ML experience.

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