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Alberta Innovates

Data Science Lead

AB, Canada
Edmonton, AB, Canada

Pay: The minimum starting salary for this position is $88,600 annually.
Job type: Full-time
Apply by: Oct 24, 2026
Experience: 7 years of progressively responsible experience in data science, machine learning, or applied AI, including experience taking solutions into production.
Posting language: English
Posted: Sep 24, 2026

Apply About employer

Applications open in a new tab.

Original job description

Employment Status: Full-time - Permanent

Location: Edmonton, Edmonton Research Park Facility

Work Model: Hybrid

About The Opportunity

The Data Science Lead is an opportunity to be part of a professional, purpose-driven team that values collaboration, innovation, accountability, and continuous improvement. Most importantly, your work will contribute to meaningful outcomes that make a difference for Albertans and help shape the future of our province.

Key responsibilities in the role of Data Science Lead include:

AI/ML Use-Case Delivery (End-to-End)

Partner with business and program teams to identify, scope, and prioritize high-value use cases, translating business objectives into measurable ML/AI outcomes.
Lead the full lifecycle - problem framing, data preparation, modelling, validation, and deployment - for the AI/ML use cases they lead, across classical ML and generative/LLM applications.
Apply MLOps/LLMOps practices for their own solutions and partner with platform and engineering teams for production hardening, CI/CD, and monitoring.
Measure and communicate the accuracy, business value, and risk of deployed solutions.

Generative & Agentic AI Development and Deployment

Design, build, and deploy agentic AI solutions on Microsoft Copilot (e.g., Copilot Studio / Azure AI Foundry) and Anthropic Claude (Claude API / Claude Agent SDK), using tool/function calling and Model Context Protocol (MCP).
Implement closed-loop LLM systems - retrieval-augmented generation (RAG), evaluation loops, guardrails, and human-in-the-loop feedback - operated within controlled or private environments.
Recommend standards for prompt design, retrieval quality, evaluation, and guardrails, and apply them to their solutions.
Configure agent triggers, permissions, and human oversight consistent with standards set with Cybersecurity and Data Governance.

Model Development & Fine-Tuning on Internal Compute

Train, fine-tune, and evaluate models - including open-weight LLMs - on internal / private compute where data residency or privacy requires it, using parameter-efficient methods (e.g., LoRA/QLoRA).
Work with Infrastructure and Platform teams to provision and right-size the compute required, rather than owning the GPU environment.
Follow the organization's data-classification policy and work with Data Governance on training-data access and de-identification.

AI Literacy & Enablement

Contribute to organizational AI literacy through role-based enablement sessions, executive briefings, and a data-science community of practice, in partnership with People/HR and Learning & Development.
Promote approved-tool boundaries and safe data-handling practices.
Mentor analysts and technical staff and build shared tooling and reusable assets that raise data-science maturity.
Represent the data-science perspective in cross-functional discussions.

Responsible AI & Continuous Improvement

Apply responsible-AI practices (fairness, transparency, documentation, human oversight) and support algorithmic-impact assessments led by the governance and privacy function.
Monitor emerging models, tools, and methods and recommend improvements.
Provide technical input to evaluations of data science, ML, and AI tools and platforms.
Collaborate with Data Governance, Cybersecurity, Enterprise Architecture, Privacy, and Infrastructure to keep solutions secure, compliant, and well-governed.

What You Need to Thrive in This Role

Diploma in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Systems, or a related discipline.
7 years of progressively responsible experience in data science, machine learning, or applied AI, including experience taking solutions into production.
Demonstrated end-to-end delivery of AI/ML use cases (from discovery through production) with measurable business value required
Demonstrated experience developing and deploying agentic AI using Microsoft Copilot and Anthropic Claude (including tool/function calling and MCP) required.
Demonstrated experience implementing closed-loop LLM systems (RAG, evaluation loops, guardrails, and human-in-the-loop feedback) required.
Demonstrated experience fine-tuning models on internal / private compute (e.g., LoRA/QLoRA) where data residency requires it required.
Demonstrated experience building AI literacy in an organization (role-based enablement, executive briefings, or a community of practice) required
Experience in public-sector, quasi-government, or research environments considered an asset.
Certifications in cloud or AI/ML platforms (e.g., Microsoft Azure AI Engineer Associate, Azure Data Scientist Associate, Databricks) considered an asset.
Credentials related to responsible AI or model governance considered an asset.
Strong applied knowledge of machine learning and statistical methods and of the generative-AI stack (LLMs, RAG, embeddings and vector databases, agents, and MCP).
Working knowledge of MLOps/LLMOps concepts (deployment, monitoring, evaluation) sufficient to collaborate with platform and engineering teams and hand off cleanly.
Working knowledge of model fine-tuning, including open-weight models and parameter-efficient methods (LoRA/QLoRA).
Understanding of responsible AI, human oversight, and algorithmic-impact assessment, and awareness of privacy, security, and data-classification requirements in a public-sector environment.
Ability to translate ambiguous business problems into well-scoped, deployable AI/ML solutions and to measure their value.
Effective communication and facilitation skills; ability to influence without authority and translate technical concepts for non-technical audiences.

Who We Are

Alberta Innovates is the province’s most comprehensive research and innovation agency. From funding to commercialization, we are Alberta’s innovation engine. We foster and accelerate research and innovation to support entrepreneurs and drive economic growth for the benefit of Albertans.

What We Offer

At Alberta Innovates we believe our people are our greatest asset. That's why we offer a comprehensive total rewards package that supports your career growth, wellbeing, and work-life balance.

Competitive compensation aligned with our internal career framework and pay structures
Comprehensive health, dental, and pension benefits to support you and your family
Professional development and learning opportunities to help you grow and advance your career
A collaborative and inclusive workplace where diverse perspectives are valued and every contribution matters
Flexible work arrangements, where operationally appropriate, along with vacation and earned time off to rest, recharge and help you bring your best self to work.

The minimum starting salary for this position is $88,600 annually. Placement within the salary range will be based on the successful candidate's qualifications, relevant experience, and internal equity.

How to Apply

Interested and qualified applicants are encouraged to submit their resume and cover letter prior to the application deadline of October 16, 2026.

The successful candidate will be required to undergo a security clearance and provide credible references.

Privacy Statement

The personal information collected in the application process is for recruitment and hiring purposes only. This collection is authorized under section 4(c) of the Protection of Privacy Act.

Employment Equity

Alberta Innovates is committed to the principle of equity in employment and encourages applications from all qualified individuals. We thank all applicants for their interest; however, only those selected for an interview will be contacted.

Additional Information

This recruitment process does not use artificial intelligence (AI) to screen, assess, or select candidates. All hiring decisions are made by human reviewers.

If you are selected for an interview, please note that recording the interview or using AI tools or assistance during the interview is not permitted.

Apply About employer

More about this job

Responsibilities

Lead AI/ML use cases from discovery and problem framing through modeling, validation, deployment, and measurement of business value. Develop and deploy agentic and closed-loop LLM solutions, support private-compute model fine-tuning, promote AI literacy, and collaborate on responsible, secure, and well-governed AI practices.

Requirements

Requires a diploma in a relevant technical or quantitative discipline and at least seven years of progressively responsible data science, machine learning, or applied AI experience, including production delivery. Candidates must demonstrate end-to-end AI/ML delivery, agentic AI development with Microsoft Copilot and Anthropic Claude, closed-loop LLM systems, private-compute fine-tuning, and organizational AI enablement.

Skills

Machine Learning
Generative AI
Agentic AI
Microsoft Copilot
Anthropic Claude
Retrieval-Augmented Generation
Model Context Protocol
MLOps
LLMOps
Model Fine-Tuning
LoRA/QLoRA
Responsible AI
Statistical Methods
Data Governance
Communication
Mentoring

Benefits

Health Benefits
Dental Benefits
Pension Benefits
Professional Development
Flexible Work Arrangements
Vacation
Earned Time Off

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Data Science
Generative AI
Large Language Models
Microsoft Copilot
Copilot Studio
Azure AI Foundry
Anthropic Claude
Claude API
Claude Agent SDK
Tool Calling
Model Context Protocol
Retrieval-Augmented Generation
Embeddings
Vector Databases
MLOps
LLMOps
LoRA
QLoRA
Open-Weight Models
Human-in-the-Loop
Responsible AI
Algorithmic-Impact Assessment
Data Governance
Cybersecurity
Privacy
Data Classification
Azure AI Engineer Associate
Azure Data Scientist Associate

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