Principal Applied Scientist - ZMS (all genders)
Tasks
- Advance auction and mechanism design capabilities
- Drive long term scientific and execution roadmap for ad tech bidding optimization
- Lead R and D real time bidding and allocation algorithms
- Mentor senior team members
- Translate business constraints into mathematical objective functions
Perks/Benefits
- Employee shares program
- Family services
- Health and wellbeing options
- Hybrid working model
- Mental health support
- Paid volunteering days
- Peer-to-peer review
- Relocation assistance
- Training platform
- Up to 60 percent remote per week
- Work from abroad
Skills/Tech-stack
Auction theory | Bayesian Inference | Control Theory | Data Pipelines | Dimensional data | Distributed Systems | High Dimensional Data | Incrementality | Large Scale Distributed Systems | Large-scale | Machine Learning | Mechanism design | Multi-Objective Optimization | Objective optimization | Optimization | Python | Reinforcement Learning | Scale distributed systems | Sparse data | Value-Based Bidding | Value-based
Education
N/A
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