Staff Applied Scientist (Perm or Contract)
Core
Design and build models for campaign optimisation, inventory allocation, and audience quality modelling in programmatic advertising to improve CTR, CPA, and ROAS.
Role type
Staff Applied Scientist (Technical Leadership)
Builds
Real-time optimisation systems for campaign performance, audience scoring, and inventory pricing/allocation
Domain
Programmatic advertising, data collaboration, privacy-preserving analytics
Deliverable
production ML models
Required skills
optimisation or bidding systems in programmatic advertising, applied ML and statistical foundations, production ML experience, fluency with programmatic ecosystem (bid requests, win notifications, signals), cross-publisher or cross-supply optimisation experience, privacy-constrained environment experience
Preferred skills
cross-publisher or cross-supply optimisation, privacy-constrained environments (cohort-based targeting, clean rooms)
Technologies
Scala, SDKs, data pipelines
Responsibilities
Design and build models for campaign optimisation using publisher-side and advertiser outcome data; Develop approaches to inventory allocation accounting for audience quality and supply dynamics; Own models end-to-end from conception through production monitoring; Influence product direction by identifying opportunities and framing feasibility; Run experiments and prototypes to validate ideas and evolve them into production systems
