Senior/Staff Applied Machine Learning Scientist

StackAdapt

2d•$160,000 - $220,000•Remote

About The Position

StackAdapt is hiring a Senior/Staff Applied Machine Learning Scientist to join its engineering team and expand its data science efforts. The company’s marketing platform processes millions of requests each second and makes billions of decisions, using machine learning and scalable technologies to serve advertisers and publishers worldwide. This is a remote-first role open to candidates located anywhere in the United States or Canada. The scientist will lead development and optimization of advanced machine learning algorithms to improve advertising effectiveness and return on investment. The role owns end-to-end development of production-grade models, including efficient, scalable code and collaboration with Machine Learning Engineers to deploy algorithms into live systems. It also leads prototyping and rigorous testing of algorithms and data pipelines with historical data, followed by iterative, data-driven improvements. The position requires at least three years of industry experience and a master’s degree or PhD in a relevant field. Compensation is based on location and other relevant factors. The listed base salary bands are CAD $170,400–$234,300 for Canada and USD $160,000–$220,000 for the United States. Additional compensation may include bonuses, commissions, or equity awards, depending on the role. Benefits and perks vary by country and engagement type.

Requirements

At least 3 years of industry experience.
Master’s degree or PhD in Computer Science, Statistics, Operations Research, or a related field.
Ability to break an ambiguously defined task into actionable steps.
Comprehensive understanding of statistics, optimization, and machine learning.
Proficiency in coding, data structures, and algorithms.
Enjoy working collaboratively with others.

Nice To Haves

Dual degrees are a plus.

Responsibilities

Lead the creation and optimization of advanced machine learning algorithms to enhance advertising effectiveness and ROI.
Own end-to-end development of production-grade machine learning models, writing efficient, scalable code.
Collaborate with Machine Learning Engineers to deploy and integrate algorithms into live systems.
Drive 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.

Benefits

Highly competitive salary.
Retirement, 401(k), or pension savings, depending on location.
Paid time off packages, including birthdays off.
Access to a comprehensive mental health care program.
Health benefits from the first day of employment.
Work-from-home reimbursements.
Optional global WeWork membership; offices or hubs in London and Toronto.
Training and onboarding program.
Support for personal development initiatives, including conferences, courses, and books.
Access to StackAdapt programmatic courses and certifications.
Parental leave program.
Social and team events.