About the position
We're looking for a Senior Applied Scientist II to join our Machine Learning Team for Growth. In this role, you'll lead initiatives focused on leveraging machine learning to drive business growth across multiple channels-think email, push notifications, and paid advertising. You'll be pioneering new solutions from the ground up, staying abreast of the latest research, and owning the end-to-end ML lifecycle-from data extraction to production deployment. This is a full-time position reporting to the Engineering Manager, Ranking Recommendations. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy.
Responsibilities
- Take solutions from 0 to 1: You'll be comfortable working in ambiguous problem spaces, experimenting, and driving projects from an initial idea to a fully operational ML product.
- Drive business growth through ML: Build and iterate on models that will inform campaigns and strategies for email marketing, push notifications, and paid media efforts.
- Stay current with research: Read cutting-edge ML and AI papers and bring innovative, impactful techniques to solve real-world problems.
- Productionize ML solutions: Develop robust systems for training, deploying, and monitoring ML models at scale.
- Collaborate cross-functionally: Work closely with Applied Scientists, Data Engineers, Product Managers, and other stakeholders to align projects with broader product goals.
- ETL and data analysis: Own critical data pipelines, perform exploratory analysis, and ensure data quality and reliability.
- Experimentation and measurement: Design and execute A/B tests to measure the effectiveness of ML-driven features, iterating quickly based on findings.
Requirements
- Proven track record in ML: You have 3+ years of experience building and deploying ML solutions.
- Strong coding skills: You write robust, production-quality code (Python, Scala, Java, or equivalent).
- Hands-on experience across the pipeline: From data extraction and preprocessing to training, evaluating, and deploying models in production environments.
- Comfort in ambiguity: You excel in situations where the scope is not fully defined, proactively finding clarity and driving forward.
- Collaboration and communication: You can articulate complex concepts to both technical and non-technical audiences and enjoy working on cross-functional teams.
Nice-to-haves
- Experience in search or recommender systems: Preferred but not required.
- Advanced degree in ML or related field: Preferred but not required.
Benefits
- Equity package
- Annual performance bonus
- Competitive benefits that support you and your family
A Smarter and Faster Way to Build Your Resume