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Machine Learning Finance Jobs in Alberta (NOW HIRING)

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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 Jun 13, 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 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 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
Infographic showing various Machine Learning Finance job openings in Alberta as of June 2026, with employment types broken down into 48% Full Time, 50% Part Time, 1% Temporary, and 1% Contract. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $115,779 per year, or $55.7 per hour.

Machine Learning Engineer (BFSI) - MLEBAS

NavitasPartners

Edmonton, AB

CA$30/hr

Full-time

Posted 9 days ago

Job description

Job Title: Machine Learning Engineer (BFSI)

Position Overview:
The ML Engineer will develop, deploy, and optimize machine learning solutions supporting fraud detection, risk analytics, customer intelligence, and financial forecasting.

Key Responsibilities:

  • Develop machine learning models and pipelines.
  • Build feature engineering frameworks.
  • Deploy production-grade ML solutions.
  • Optimize model performance and scalability.
  • Collaborate with data scientists and business teams.
  • Implement model monitoring and governance.

Required Skills:

  • Python
  • Machine Learning
  • Scikit-learn
  • TensorFlow
  • PyTorch
  • Spark ML
  • Feature Engineering
  • Model Deployment
  • SQL

Required Qualifications:

  • Bachelor's or Master's degree in Data Science, AI, Computer Science, or related field.
  • 5+ years of machine learning experience.

Mandatory Industry Experience:

  • Must have prior BFSI experience delivering fraud detection, credit risk scoring, customer segmentation, anti-money laundering, underwriting, or financial forecasting solutions.

For more details reach at resumes@navitassols.com