Machine Learning Scientist

About the company

• This position is listed on behalf of a partner company managing all applications and next steps.
• Highly technical engineering and data science environment processing millions of requests every second.

Responsibilities

• Design, develop, and improve machine learning algorithms that optimize advertising performance and maximize return on investment.
• Explore novel algorithmic approaches and apply established machine learning techniques to complex optimization problems.
• Build prototypes of algorithms and data pipelines, test performance using historical datasets, and iteratively refine solutions.
• Translate successful research and prototypes into reliable, production-ready code for large-scale, high-throughput environments.
• Work closely with engineering and data engineering teams to integrate new algorithms.
• Apply statistical methods, optimization techniques, and machine learning principles to evaluate performance.
• Decompose ambiguous technical challenges into actionable research questions, experiments, and implementation plans.
• Contribute to scalable solutions supporting high-volume data processing and decision-making.

Requirements

• Master’s degree or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field.
• Comprehensive understanding of machine learning concepts and techniques.
• Strong knowledge of statistics, probability, mathematical optimization, and quantitative reasoning.
• Strong coding skills and solid understanding of data structures and algorithms.
• Ability to design, prototype, test, and refine algorithms using historical data.
• Strong analytical and problem-solving skills.
• Ability to work independently and in a remote-first organization.
• Undergraduate degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or related field.

Conditions

• Canadian base salary range of CAD $140,000–$192,500 (final offer based on experience, skills, education, qualifications, location, business needs).
• Additional compensation may include annual bonuses, equity awards, or other incentives.
• Remote-first work environment with coworking space access for eligible employees.
• Retirement/pension/savings programs depending on country of employment.
• Competitive paid time off, including a birthday day off.