Retention Science is looking for an experienced full-stack Ruby on Rails engineer who is passionate about writing clean, well-tested code. You’ll be working on our “product squad” - the team that drives our newest application features into production and ensures that our product is moving forward to the delight our clients. You will be building out the robust applications that schedule, optimize, and automate marketing campaigns powered by our data science and machine learning models. The tools you build will communicate across external and internal service APIs to help our clients visualize and interact with their data (millions of users and data points.) You'll get to work across the stack - front-end, back-end, and across our micro-services and distributed systems. You should love working with RoR, although you’ll also have opportunity to work on other services, frameworks, languages (eg. Node.JS, Scala, Angular, Backbone). In addition you will gain exposure into the machine learning stack (Spark, Hadoop frameworks) that our data scientists have developed to predict and personalize at scale.
In addition to having meaningful responsibilities and improving your engineering chops, you will also receive comprehensive exposure to all aspects of our business. The code and ideas that you contribute will have a tangible impact on the cumulative work of the team as a whole. You thrive in a small, dynamic team environment and want to make an impact in a fast-paced start-up environment.
We’ve been named in CRN’s Top 10 Big Data Startups of the Year, Fast Company’s “Innovation Agents” of 2013, SocialTech’s Top 10 Software Company in Southern California, and one of Fox News LA’s most promising startups to watch. Our founders have received awards like the Ernst & Young Entrepreneur of the Year. We come from schools like Berkeley, Caltech, Carnegie Mellon, Stanford, and Yale. We’ve been featured in the Wall Street Journal, Forbes, Entrepreneur, Inc. Magazine, TechCrunch, Bloomberg, and Reuters, among other notable publications.
Our powerful profiling engine uses machine learning techniques and statistical models to analyze purchasing trends based on massive data sets, which we then use to predict customers' behavior and maximize customer retention for our clients. We love creative brainstorming for solutions and the pursuit of innovation-fueled knowledge.
We also like long walks on the beach, the crackle of turning Rubik's cubes, and dogs with old-soul eyes. Because who doesn't?