TripAdvisor, the world’s largest travel site, is looking for a talented engineer to join our Data Science Platform team in Needham.
In this role, you’ll work with our Engineering and Data Science teams to drive and support large-scale machine learning for a range of products across multiple platforms. TripAdvisor uses machine learning across many aspects of its business. We are growing to support the challenges of scaling our tools both to massive volumes of data and to a high throughput of projects from a large team of scientists. As a Data Science Platform Engineer, you will contribute to defining the long-term platform roadmap and design solutions that operate at scale and have cross-team buy-in. You’ll be a hands-on contributor with the goal of delivering better insights into our users’ behavior while shipping models into production.
Can you operate in a highly iterative agile development environment? Can you interact with a wide variety of peers across the organization to get to a single result? Can you deliver fast results? Are you, above all else, passionate about what you do and whom you do it for?
You have a solid track record of gathering and creating new ideas, implementing and gaining adoption across the organization. 3+ years of experience required.
You have experience building applications or tools using large-scale big data infrastructure. Hadoop, Spark, and BigQuery experience are very useful.
You have experience developing container-based applications and working in a clustered environment. Familiarity with Docker and Kubernetes are a plus.
You have experience with software development in Python.
You are comfortable working in SQL and Java. Experience with ETL tooling/coding, workflow tools, and hive is a real plus.
Basic knowledge of machine learning techniques is highly desired (e.g., cross-validation, model fitting, clustering, regression, classification).
You are comfortable with server-side programming. Web and client-side programming is a plus.
You are strong in the ways of Computer Science and can analyze and propose algorithms based on complexity.