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Head Data Science Jobs in Alberta (NOW HIRING)

If you're in that space, or want to head that direction, this role will be a great fit. You will ... Clearly define KPI's with internal Marketing Data Science Analyst and client to establish correct ...

If you'rein that space, or want to head that direction, this role will be a great fit. You will ... Clearly define KPI's with internal Marketing Data Science Analyst and client to establish correct ...

If yourein that space, or want to head that direction, this role will be a great fit. You will love ... Clearly define KPIs with internal Marketing Data Science Analyst and client to establish correct ...

Resource Geologist

Calgary, AB

CA$102K - CA$120K/yr

Edmonton Regional Office or Calgary Head Office, AB Employment Type: Full Time - Limited Term ... Prepare and present scientific findings, data products, and workflow recommendations for internal ...

Resource Geologist

Edmonton, AB

CA$102K - CA$120K/yr

Edmonton Regional Office or Calgary Head Office, AB Employment Type: Full Time - Limited Term ... Prepare and present scientific findings, data products, and workflow recommendations for internal ...

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Showing results 1-20

Head Data Science information

See Alberta salary details

$22.5K

$110.1K

$204K

How much do head data science jobs pay per year?

As of Jul 27, 2026, the average yearly pay for head data science in Alberta is $110,123.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,000.00 and $149,000.00 per year, depending on experience, location, and employer.

How to become head of data science?

To become a head of data science, professionals typically need extensive experience in data analysis, machine learning, and leadership roles, often requiring 8-10 years in data-related positions. A strong educational background in computer science, statistics, or related fields, along with skills in programming, data management, and strategic planning, is essential. Advanced degrees and certifications in data science or analytics can also enhance prospects for leadership positions.

Is 40 too late for data science?

The Head Data Science role and similar data science positions do not have strict age limits; many professionals transition into data science later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning, regardless of age.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Chief Data Officer, Director of Data Science, or Lead Data Scientist, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 for those with extensive experience, advanced skills in machine learning, and industry expertise. These roles typically require strong leadership, strategic thinking, and proficiency with tools like Python, R, and cloud platforms.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What does a Head of Data Science do?

A Head of Data Science is responsible for leading and managing the data science team within an organization. They oversee the development and implementation of data-driven strategies, ensuring that the team delivers valuable insights and predictive models to support business goals. This role involves collaborating with other departments, setting the vision for data initiatives, and ensuring best practices in data analysis and machine learning are followed. Additionally, the Head of Data Science often mentors team members and helps shape the organization's overall data strategy.

What are some common challenges faced by a Head of Data Science when building and leading a data science team?

As a Head of Data Science, one of the main challenges is balancing strategic leadership with hands-on technical guidance. You'll often need to align the team's goals with broader business objectives while ensuring that team members have the right mix of skills and resources. Additionally, fostering effective collaboration between data scientists, engineers, and business stakeholders can be complex, especially in cross-functional environments. Managing expectations around project timelines and communicating technical insights in a clear, actionable way are also key aspects of the role.

What are the key skills and qualifications needed to thrive as a Head of Data Science, and why are they important?

To thrive as a Head of Data Science, you need advanced expertise in statistics, machine learning, data modeling, and a strong background in computer science or a related quantitative field, often supported by a master's or Ph.D. Proficiency with programming languages like Python or R, big data platforms such as Hadoop or Spark, and familiarity with cloud-based analytics tools are typically required. Strategic leadership, excellent communication skills, and the ability to mentor and inspire teams are crucial soft skills for this role. These abilities are essential to drive data-driven decision-making, foster innovation, and align analytics initiatives with organizational goals.

What is the difference between Head Data Science vs Data Science Manager?

AspectHead Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project delivery, coordinating data science projects
Required SkillsAdvanced analytics, leadership, strategic planningTeam management, technical expertise, project management
ExperienceSenior data science background, leadership rolesData science experience with managerial responsibilities
Work EnvironmentExecutive level, cross-departmental collaborationTeam-focused, project-oriented

The Head Data Science typically holds a strategic, leadership role overseeing the entire data science function, while the Data Science Manager focuses on managing teams and project execution. Both roles require strong technical backgrounds, but the Head Data Science emphasizes vision and strategy, whereas the Data Science Manager concentrates on operational management.

What are the most commonly searched types of Data Science jobs in Alberta? The most popular types of Data Science jobs in Alberta are:
Infographic showing various Head Data Science job openings in Alberta as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $110,123 per year, or $52.9 per hour.

AI Scientist & Engineer, Assurance Innovation Lab

BDO Canada

Edmonton, AB • Hybrid

Full-time

PTO

Posted 5 days ago


Job description

Putting people first, every day

BDO is a firm built on a foundation of positive relationships with our people and our clients. Each day, our professionals provide exceptional service, helping clients with advice and insight they can trust. In turn, we offer an award-winning environment that fosters apeople-first culturewith a high priority on your personal and professional growth.

Your Opportunity

We are looking for an exceptionally skilled, hands-on, and innovation-minded AI Scientist & Engineer to bridge the gap between advanced data science, experimental machine learning, and scalable enterprise software engineering in our new Assurance Innovation Lab.

The Assurance Innovation Lab (ASR Labs) serves as the experimentation, innovation, and solution development engine supporting our practice. Working alongside other functions nationally - including our Innovation Operations, AI Studio - Central Lab, Central Data Team, and Innovation & Change (I&C) - you will help ideate, design, prototype, develop, and deliver scalable solutions that modernize how work gets done across our Assurance practice.

In this net new role, you will work with a team dedicated to building modern applications, intelligent workflow solutions, integrations, and AI-enabled platforms that support business transformation and operational modernization initiatives across our practice. You will be reporting to our Head of ASR Transformation, and have a dotted line to our technically astute managers in our AI Studio - Central Lab.

This hybrid role is responsible for extracting high-value insights from complex datasets, training custom large language models (LLMs), and designing, building, and deploying production-grade agentic workflows and retrieval-augmented generation (RAG) solutions. Operating under enterprise governance frameworks like ISO/IEC 42001 and the NIST AI Risk Management Framework (AI RMF), you will deliver responsible, scalable, and highly impactful AI systems that drive true business transformation.

The ideal candidate for this role will have 3-5 years of hands-on experience building, fine-tuning, deploying, and monitoring machine learning models and Generative AI solutions in an enterprise production environment. This role rests on the ability to work cross-functionally with AI Architects, AI Studio Leads, ML Engineers, Data Scientists, Full Stack Developers, and citizen developers on firm-wide strategic initiatives.

Key Responsibilities:

AI, Machine Learning & Advanced Analytics

  • Design, build, train, and optimize machine learning and AI models to support Assurance transformation initiatives

  • Develop intelligent solutions leveraging NLP, generative AI, knowledge graphs, predictive analytics, and automation capabilities

  • Support experimentation and prototyping of emerging AI technologies and use cases within Assurance

  • Evaluate model performance, explainability, reliability, and responsible AI considerations

  • Contribute to development of scalable AI-enabled workflows and intelligent operational solutions

Cross-Functional Collaboration & Business Partnership

  • Partner closely with Transformation Relationship Managers (TRMs), Assurance practitioners, Innovation & Change (I&C), Data & Analytics, and leadership teams

  • Contribute to multidisciplinary teams focused on solving business problems through technology, AI, automation, and workflow redesign

  • Support rapid experimentation, prototyping, and scaling of innovative solutions within the Assurance R&D Lab

  • Help bridge strategy, business operations, and technical execution to accelerate transformation outcomes

  • Translate complex business problems into practical analytical and AI-driven solutions

  • Participate in discovery sessions, design thinking workshops, ideation activities, and working groups

Data Engineering & Platform Enablement

  • Collect, clean, transform, and analyze large and complex datasets from multiple sources

  • Build and maintain scalable data pipelines and model integration frameworks

  • Support connected data and intelligence capabilities aligned to the broader Total Assurance Ecosystem strategy

  • Work with cloud-based environments and modern AI infrastructure to support scalable deployment and operationalization

  • Collaborate with engineering teams to productionize and operationalize solutions

Innovation & R&D Collaboration

  • Work closely with the Assurance R&D Lab to validate concepts, prototype solutions, and scale successful initiatives

  • Stay informed on emerging trends across AI, automation, Assurance technology, data science, and intelligent systems

  • Help evaluate external tools, platforms, and ecosystem opportunities relevant to Assurance Transformation

  • Contribute to a culture of experimentation, innovation, and continuous improvement

Requirements

  • Programming Languages: Expert-level Python is required. Professional proficiency in R, Scala, Java, or TypeScript is highly desirable

  • AI & LLM Frameworks: Deep experience with OpenAI API, Anthropic, Hugging Face, LangChain, LlamaIndex, and LangGraph

  • Data Science & Deep Learning: Comprehensive experience with PyTorch, TensorFlow, Scikit-Learn, Pandas, NumPy, and Matplotlib

  • Model Training: Practical knowledge of training and fine-tuning open-source LLMs/transformers (e.g., Llama, Mistral) and implementing Knowledge Graphs

  • Data & Vector Infrastructure: Hands-on experience with Pinecone, Milvus, Weaviate, and standard SQL/NoSQL databases

  • DevOps / MLOps: Advanced proficiency with Docker, Kubernetes, Nvidia Triton Inference Server, and MLOps tracking platforms (MLflow, Weights & Biases)

  • Cloud Platforms: Strong working knowledge of enterprise cloud environments including Microsoft Azure (Azure AI / AI Foundry), AWS (Bedrock), or GCP

  • Architecture & Patterns: Demonstrated mastery of Retrieval-Augmented Generation (RAG) architectures and multi-Agent AI design patterns

Ideal Candidate Will Have

  • A systematic approach to problem-solving and devising practical solutions for complex enterprise bottlenecks

  • Published academic research in top-tier ML/AI conferences/journals OR demonstrated practical excellence through Kaggle competitions

  • High passion for translating complex data and multi-agent system capabilities into tangible, actionable business value

  • Strong business curiosity and problem-solving mindset

  • Passion for applying AI and data science to practical operational challenges

  • Ability to balance experimentation with scalable execution

  • Strong collaboration and stakeholder engagement skills

  • Interest in workflow modernization, intelligent automation, and future-state operating models

  • Passion for continuous learning and emerging technologies

Why Join the Assurance Innovation Lab?

This is an opportunity to help build the future of Assurance through modern platforms, intelligent workflows, and scalable AI-enabled solutions.

You will join a high-performing team to work on high-impact transformation initiatives that directly influence how the business operates and delivers value.

The role offers exposure to:

  • Enterprise transformation and innovation programs

  • AI-enabled applications and intelligent workflow solutions

  • Modern cloud and engineering ecosystems

  • Cross-functional collaboration with Assurance, AI-Studio, Data & Analytics, Innovation & Change, and leadership teams

  • Rapid experimentation and enterprise-scale delivery initiatives

  • Most importantly, you will help create practical solutions that improve how work gets done across our Assurance practice


Why BDO?
Our people-first approach to talent has earned us a spot among Canada's Top 100 Employers for 2026. This recognition is a milestone we're thrilled to add to our collection of awards for both experienced and student talent experiences.


At BDO, our people experience is guided by three core pillars-Do work with genuine care, Do what matters with purpose, and Do what's next - shaping how we support our people, serve our clients, and grow together.

Our firm is committed to providing an environment where you can be successful in the following ways:

  • We enable you to engage with how we change and evolve, being a key contributor to the success and growth of BDO in Canada.
  • We help you become a better professional within our services, industries, and markets with extensive opportunities for learning and development.
  • We support your achievement of personal goals outside of the office and making an impact on your community.
  • We foster a collaborative, inclusive environment where your ideas are valued, and you can do your best work with genuine care and purpose
  • We encourage innovation and forward thinking, empowering you to embrace what's next and help shape the future of our firm

Giving back adds up:Where company meets community.BDO is actively involved in our communities by supporting local charity initiatives. We support staff with local and national events where you will be given the opportunity to contribute to your community.

Total rewards that matter: We pay for performance with competitive total cash compensation that recognizes and rewards your contribution. We provide comprehensive benefits from day one, and a flexible personal time off policy. We're committed to supporting your overall wellbeing and provide reimbursement for wellness initiatives that fit your lifestyle.

Everyone counts:
We are committed to creating a workplace where employees can participate fully, contribute meaningfully and succeed without barriers. We are dedicated to fostering a workplace defined by respect, fairness, and a true sense of belonging for everyone. We recognize and celebrate the unique experiences, identities, and perspectives that each of us bring - and that these experiences strengthen how we work together. Our commitment extends to ensuring that our application process is both inclusive and accessible. If you require accommodation to complete the application process, please contact us.


Flexibility:
All BDO personnel are expected to spend some of their time working in the office, at the client site, and virtually unless accommodations or alternative work arrangements are in place.

Our model is a blended approach designed to support the flexible needs of our people, the firm and our clients. It's about creating work experiences that meet everyone's needs and providing flexibility to adjust when, where and how we work to meet the expectations of our role.

Code of Conduct: Our Code of Conduct sets clear standards for how we conduct business. It reflects our shared values and commitments and includes guiding principles to help us make ethical decisions and maintain trust with each other, our clients, and the public.

BDO may use artificial intelligence enabled tools to support certain aspects of the recruitment process. While these tools assist our teams, our use of AI does not replace human decision making, and all employment-related outcomes are made by BDO personnel.

More information on BDO Canada's Privacy Policy can be found here:

Privacy Policy | BDO Canada


Ready to make your mark at BDO? Click "Apply now" to send your up-to-date resume to one of our Talent Acquisition Specialists.


To explore other opportunities at BDO, check out ourcareers page.


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