We are a New York City startup with a mission to help the world's top publishers and advertisers make smarter decisions through real-time data that matters. Our analytics and intelligence software is used by clients including The New York Times, Condé Nast, Kellogg’s, Forbes, and The Wall Street Journal. We are a SaaS company and we are venture-backed by several top Silicon Valley and New York investors. Our founding team has worked together for over 10 years and previously partnered to create Right Media, which was acquired by Yahoo in 2007.
About the Opportunity
- Design and implement systems to process and aggregate terabytes of streaming data in real time.
- Build micro-services and APIs that facilitate data processing and expose Moat data to our clients
- Classify and analyze data using both automated and crowd-sourced approaches.
- Build predictive models for fraud detection and ad performance optimization
- Write applications for real-time ad decisioning that run on geographically distributed clusters
- BS, MS, or PhD in computer science, engineering or other related field
- 2+ years experience with data-intensive backend programming
- You have strong understanding of statistics
- Depth experience in one or more of the following areas--Data science and analysis, distributed data processing, complex web-app design, and / or cloud infrastructure design (AWS)
- You understand experimental design, and can build for measurement and interpretation of results
- You write clean, well-structured, production-quality code in Python
- Strong Bash, and Linux systems skills
- You have built and deployed large-scale distributed data processing pipelines
- Ability to design and deploy lightweight web services that are scalable and fault-tolerant
- Familiarity with various data processing and storage technologies including Postgres / Vertica / Redshift, Dynamo DB, Redis, Kinesis, and MapReduce
- Passion for extracting insights from large volumes of data
About the Team
- We are passionate, excited, and thrive in a fast paced culture.
- We love sharing our knowledge and learning about new technologies.
- We are the type of people who take risks when looking for novel and creative solutions to complex problems.
- We care about solving big-picture, systemic problems—looking beyond the surface to understand root causes so that we can build complete and long-term solutions.
All offers for employment with Moat are contingent upon successful completion of a background check.
Our organization participates in E-Verify.