Remote Applied ML Scientist to Boost Campaign ROI

StackAdapt Inc.; New York (NY); Remote; USD 128,000 - 176,000; Full time

Benefits offered by this job

Competitive salary

401K/ Pension

Generous PTO

Mental health care program

Health benefits from day one

Work from home reimbursements

WeWork option

Training & onboarding

Professional development

Parental leave

Job summary

StackAdapt is hiring an Applied Machine Learning Scientist to join our engineering team. You will develop and refine machine learning algorithms for our high-volume ad platform, write production-grade code, and prototype pipelines using real-world data.

We value collaboration and rigorous experimentation across traffic, data storage, and scalability concerns. The role offers a remote-first work setup for North America, with competitive base salary bands for USA/Canada, and a focus on delivering

Qualifications

• Master's degree or PhD in Computer Science, Statistics, Operations Research or related field.
• Ability to take ambiguously defined tasks and break into actionable steps.
• Strong understanding of statistics, optimization and machine learning.
• Proficient in coding, data structures, and algorithms.
• Enjoy working in a friendly, collaborative environment.

Responsibilities

• Innovate ML algorithms to maximize ROI and advertising performance.
• Write production code, collaborating with Data Engineers to implement novel ML algorithms.
• Prototype potential algorithms and pipelines, test with historical data, iterate based on insights.

Skills

Statistics

Optimization

Machine Learning

Coding

Collaboration

Education

MS/PhD in CS/Stats/OR

Tools

Python

Job description

StackAdapt is hiring an Applied Machine Learning Scientist to join our engineering team. You will develop and refine machine learning algorithms for our high-volume ad platform, write production-grade code, and prototype pipelines using real-world data.

We value collaboration and rigorous experimentation across traffic, data storage, and scalability concerns. The role offers a remote-first work setup for North America, with competitive base salary bands for USA/Canada, and a focus on delivering