ZipRecruiter

Log In

1

Machine Learning Finance Jobs in Alberta (NOW HIRING)

DataVisor

Delivery Engineer - Canada

Calgary, AB

CA$80K - CA$120K/yr

Familiarity with anti-fraud concepts in the financial services or internet industry is a plus. * Exposure to real-time computing, big data technologies, or machine learning through coursework ...

Royal Bank of Canada

Staff Software Engineer

Calgary, AB · On-site

... financial institution runs its most critical AI workloads, working directly with leading researchers in machine learning while having access to rich, massive datasets and the computational resources ...

Royal Bank of Canada

Staff AI Engineer

Calgary, AB · On-site

... machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable ...

TELUS

AI Lead/Developer

Edmonton, AB

Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI * Exceptional communication skills to present technical concepts to finance stakeholders and business leaders ...

TELUS

AI Lead/Developer

Calgary, AB

Strong background in Machine Learning frameworks, GenAI platforms, LLMs, and agentic AI * Exceptional communication skills to present technical concepts to finance stakeholders and business leaders ...

TELUS

Manager AI

Calgary, AB · On-site +1

Deep technical knowledge and 3+ years of experience in deploying AI and machine learning solutions ... Demonstrated ability to quickly learn and adapt to new financial concepts and apply AI solutions ...

TELUS

Manager AI

Edmonton, AB · On-site +1

Deep technical knowledge and 3+ years of experience in deploying AI and machine learning solutions ... Demonstrated ability to quickly learn and adapt to new financial concepts and apply AI solutions ...

next page

Showing results 1-20

All JobsMachine Learning Finance JobsMachine Learning Finance Jobs in Alberta

Machine Learning Finance information

See Alberta salary details

$22K

$115.8K

$214.5K

How much do machine learning finance jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning finance in Alberta is $115,779.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What job makes $1,000,000 a year?

In the field of machine learning finance, highly senior roles such as Chief Data Officer or Quantitative Hedge Fund Manager can earn $1,000,000 or more annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, extensive experience, and expertise in algorithms, financial modeling, and programming tools like Python or R.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence or machine learning within finance or technology sectors, often involving advanced skills in data analysis, programming, and model development. Such roles may include AI research scientists, machine learning engineers, or senior data scientists, and usually require extensive experience, specialized certifications, and proficiency with tools like Python, TensorFlow, or cloud platforms.

Can machine learning be used in finance?

Machine learning is widely used in finance for tasks such as risk assessment, fraud detection, algorithmic trading, and portfolio management. Machine learning finance professionals develop models using programming languages like Python and tools such as TensorFlow or scikit-learn to analyze large datasets and improve decision-making processes.

What are the key skills and qualifications needed to thrive in the Machine Learning Finance position, and why are they important?

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What is the salary of ML in finance?

Machine Learning professionals in finance typically earn between $80,000 and $150,000 annually, depending on experience, location, and specific role. Senior roles or those with advanced skills in data analysis, programming, and financial modeling can earn higher salaries, often exceeding $200,000 with bonuses and incentives.

What are some typical challenges faced by professionals in Machine Learning Finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a Machine Learning Finance job?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

What are popular job titles related to Machine Learning Finance jobs in Alberta? For Machine Learning Finance jobs in Alberta, the most frequently searched job titles are:
What job categories do people searching Machine Learning Finance jobs in Alberta look for? The top searched job categories for Machine Learning Finance jobs in Alberta are:
Machine Learning Finance jobs near you
Manager, Machine Learning Operations (MLOps)

Manager, Machine Learning Operations (MLOps)

Wawanesa Insurance

Calgary, AB • Hybrid

CA$140K - CA$180K/yr

Other

Retirement, PTO

Posted 14 days ago

Job description

Job ID: 9789 


Employment Type: Existing Role 
Working Business Language: English 
 

Salary: At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus plan, leave of absence top-up programs and provided with generous vacation time, personal days, premium free benefits and pension plan. 
 

The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $140,000 - $180,000.  Candidates with salary expectations outside of the range are still encouraged to apply.

About Us
At Wawanesa, we offer a hybrid work environment that offers flexibility to our employees in balancing in-office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work. You may work from any of the following locations: Winnipeg, MB; Calgary, AB; Toronto (North York), ON.
 

The Wawanesa Mutual Insurance Company ("Wawanesa Mutual"), founded in 1896, is one of Canada's largest mutual insurers, with over $3.5 billion in annual revenue and assets of $10 billion (CAD). Wawanesa Mutual, with its National Headquarters in Winnipeg, is the parent company of Wawanesa Life, which provides life insurance products and services throughout Canada, and Western Financial Group, which distributes personal and business insurance across Canada. Wawanesa proudly serves more than 1.7 million members in Canada, and we are home to more than 3,300 employees distributed across the Canadian regions and communities where we operate. We give back to organizations that strengthen communities, donating more than $3.5 million annually to charitable organizations, including over $2 million annually in support of people on the front lines of climate change. We are also proud to be recognized as one of Manitoba's Top Employers. To learn more visit wawanesa.com. 


We are currently looking for dedicated, driven, and enthusiastic individuals who thrive in an environment that welcomes change and are looking for an opportunity for diverse experience and advancement on a growing team.
 

Job Overview

The Manager, Machine Learning Operations (MLOps) contributes to Wawanesa's success by bringing your passion for predictive modeling and machine learning. In this role, you will lead the Machine Learning Operations (MLOps) function, ensuring scalable, reliable, and cost-effective deployment of machine learning solutions across the enterprise. The manager is leading a team responsible for taking machine learning applications to support decision making across the organization from concept to production, with accountability for platform architecture, production reliability, governance, and lifecycle management.   

Job Responsibilties

  • Work directly with organizational leaders to introduce advanced analytics to all functions within the organization, and to foster the advancement and adoption of analytic assets.
  • Develop and advance analytic standards and processes that enable all aspects of advanced analytics including applied research, proof of concept, deployment of production grade ethical machine learning models, model monitoring and measurement.
  • Own and evolve the enterprise MLOps platform strategy, including CI/CD for ML, model registry, feature management, orchestration, monitoring, and observability frameworks.
  • Establish standardized deployment patterns and infrastructure-as-code practices to reduce bespoke solutions and increase reuse across teams.
  • Model lifecycle governance from development through validation, deployment, monitoring, retraining, and retirement.
  • Identify and organize educational initiatives aimed at the development of overall inter- and intra-departmental knowledge.
  • Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.
  • Perform other duties as assigned.
Qualifications
  • A minimum of five years of experience in developing and deploying enterprise-scale machine learning solutions, and one year of people leadership with proven ability to build high performing teams.
  • Strong business acumen with advanced analytical and problem-solving skills, with the ability to recognize, and identify critical issues.
  • Excellent interpersonal, presentation and communication skills, with the ability to effectively convey complex ideas in a simple, persuasive, and eloquent manner.
  • Comfortable confronting difficult issues and diplomatic in delivery of challenging messages.
  • Ability to establish and maintain good relationships with key stakeholders.
  • Advanced planning and organizing skills, with the ability to manage and prioritize a busy workload and multiple projects.
  • Knowledge and experience in the insurance industry is considered an asset.

#Li-Hybrid #LI-JB3


Diversity Equity, Inclusion& Belonging
At Wawanesa, we are committed to Diversity, Equity, Inclusion and Belonging (DEIB) and believe that our strength lies in the diversity of our people - this is supported by having a representative workforce.

We welcome applications from all qualified candidates, including racialized persons, women, Indigenous Peoples, persons with disabilities, members of the 2SLGBTQIA+ community, gender-diverse and neurodiverse individuals, and anyone who can contribute to the further diversification of thought and ideas. 
 

We aim to ensure our recruitment process is accessible to all candidates. If you require accommodations during any stage of the recruitment process, please reach out in confidence to jobs@wawanesa.com.
 

All Wawanesa job applicants are subject to Wawanesa's Privacy Policy.

Please note that the recruitment process for this position may involve the use of AI tools to screen, assess, or select applicants. All final decisions are taken or reviewed by human recruiters and human hiring leaders in compliance with all applicable legislation.  
 

Apply