- Company Name
- Pinterest
- Job Title
- Machine Learning Engineer / Economist, Ads Marketplace
- Job Description
-
Job title: Machine Learning Engineer / Economist, Ads Marketplace
Role Summary: Design, build, and deploy data‑driven solutions to optimize Pinterest’s marketplace. Apply economic theory, auction design, and machine learning to improve ad placement, pricing, and user experience while analyzing long‑term impacts and reducing ad fatigue.
Expactations: Deliver production‑ready statistical models and experimentation pipelines that influence marketplace parameters and ad diversification. Collaborate across engineering, product, and analytics teams to translate economic insights into scalable systems. Demonstrate strong causal inference skills through A/B testing and long‑running experiments. Maintain rigorous data integrity, model logic, and documentation in a fast‑moving environment.
Key Responsibilities:
- Build and maintain predictive models for bidder behavior, churn, and revenue forecasting.
- Tune utility functions and auction mechanisms to balance advertiser spend, user satisfaction, and marketplace health.
- Design experiments to measure short‑ and long‑term marketplace effects, including second‑order impacts of new ad formats.
- Develop strategies for pricing, bandwith allocation, and ranking to maximize overall platform value.
- Lead cross‑functional discussions on trade‑offs, policy implications, and business objectives.
- Deploy models to production, monitor performance, and iterate based on real‑world feedback.
Required Skills:
- Expertise in econometrics, auction theory, and market design.
- Proficient in Python, R, SQL, and scalable ML frameworks (TensorFlow, PyTorch, scikit‑learn).
- Deep knowledge of causal inference techniques, A/B testing, and online experimentation at scale.
- Strong software engineering practices: version control, CI/CD, unit & integration testing.
- Excellent analytical, quantitative, and problem‑solving skills.
- Ability to communicate complex concepts clearly to technical and non‑technical stakeholders.
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Economics, Operations Research, Statistics, or a closely related field.
- Professional certifications in machine learning or data science (e.g., AWS Certified Machine Learning, Google Cloud ML Engineer) are a plus.