Senior/Staff Applied Machine Learning Scientist

Lead the creation and optimization of advanced machine learning algorithms—from developing new methods to refining existing techniques—to enhance advertising effectiveness and ROI using deep ML expertise.

Own the end-to-end development of production-grade ML models: write efficient, scalable code and collaborate with Data Engineers to deploy and integrate algorithms into live systems.

Drive the prototyping and rigorous testing of innovative algorithms and data pipelines using historical data to validate performance and scalability; lead iterative improvements based on data-driven insights.

3+ years of industry experience

Have a Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.

Have the ability to take an ambiguously defined task, and break it down into actionable steps

Have a comprehensive understanding of statistics, optimization and machine learning

Are proficient in coding, data structures, and algorithms

Enjoy working in a friendly, collaborative environment with others

Highly competitive salary

Retirement/ 401K/ Pension Savings globally

Competitive Paid time off packages including birthday's off!

Access to a comprehensive mental health care program

Health benefits from day one of employment

Work from home reimbursements

Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto

Robust training and onboarding program

Coverage and support of personal development initiatives (conferences, courses, books etc)

Access to StackAdapt programmatic courses and certifications to support continuous learning

An awesome parental leave program

A friendly, welcoming, and supportive culture

Our social and team events!

Please note: Benefits and perks may vary depending on your country of employment and the nature of your engagement. In locations where StackAdapt does not have a legal entity, employment and benefits are administered in accordance with local regulations and partner policies.