Euclid Analytics | Backend & Software Engineers | San Francisco (SF), CA, ONSITE Only | euclidanalytics.com
Who we are: We're a Series C funded startup just over 30 people total and our tight-knit team is focused on using Wi-Fi data to help retailers make better decisions. We create analytics products based on substantial amounts of data–40gb/day & growing.
Roles: Euclid Analytics is looking to add Backend and Software Engineers to our backend team! We're looking for candidates who have at least one year of industry experience and who are passionate about solving hard problems.
Tech Stack includes: Scala, Python, Spark, Kafka, MySQL, Redshift, AWS, and Mesos.
Projects include: classification models to guess whether someone is visiting a store or walking by, streams for real-time alerts, simulating store traffic, helping clients improve their staffing, and calculating cross visitors across different stores. Much of our work involves figuring out how to make these calculations work in an efficient, distributed way across large datasets.
Interview process: Intro call with our tech recruiter, a phone interview with a hiring manager and a take-home technical assessment. This is followed up by a day of onsite interviews that will most likely include probability/stats questions, a deep dive on your take-home exercise answers, an ETL question, and lunch. For programming questions you're welcome to use your own laptop or one that we provide–we won't make you write code on a whiteboard!
Who we are: We're a Series C funded startup just over 30 people total and our tight-knit team is focused on using Wi-Fi data to help retailers make better decisions. We create analytics products based on substantial amounts of data–40gb/day & growing. Roles: Euclid Analytics is looking to add Backend and Software Engineers to our backend team! We're looking for candidates who have at least one year of industry experience and who are passionate about solving hard problems.
Tech Stack includes: Scala, Python, Spark, Kafka, MySQL, Redshift, AWS, and Mesos. Projects include: classification models to guess whether someone is visiting a store or walking by, streams for real-time alerts, simulating store traffic, helping clients improve their staffing, and calculating cross visitors across different stores. Much of our work involves figuring out how to make these calculations work in an efficient, distributed way across large datasets.
Interview process: Intro call with our tech recruiter, a phone interview with a hiring manager and a take-home technical assessment. This is followed up by a day of onsite interviews that will most likely include probability/stats questions, a deep dive on your take-home exercise answers, an ETL question, and lunch. For programming questions you're welcome to use your own laptop or one that we provide–we won't make you write code on a whiteboard!