Simon is a data-first marketing platform. We’re a technology-driven company on a mission to leverage big data and data science to message customers in a bespoke and responsive fashion. Our platform is built for scale, and we work with forward thinking brands including Blue Apron, TrueCar, and OpenTable.
Simon Data’s core thesis stems from a fundamental shortcoming in how big data and data science are being applied: companies are investing heavily in these efforts, yet getting them to deliver value to business functions leaves many companies scratching their heads. Rocket scientists, PhDs, and statisticians all too often sit in a corner doing “science” while the rest of the organization looks from afar. Simon seeks to bridge this gap with a platform that connects core business and product data into customer insights to power workflow automations and optimizations in email, ads, and more. Our goal is to improve and optimize customer experiences by making the entire process data-driven, from experimentation to insights to results.
As a Machine Learning Engineer at Simon, you will be responsible for building and optimizing smart systems that drive revenue—our statistical models are at the core of our product, and will only become more so as we continue to develop and add features. We take an approach to ML that is data-first, and requires principled modeling decisions: we don’t believe in theory-crafting models before we have collected the data that will power them, as well as built out the business process that will continue to generate that data. In the model building process, we prioritize interpretable models whose training and performance yield insights about the underlying process, along with optimizing the selected objective. Finally, we believe that Don Knuth was more right about machine-learning models than anything else when he said premature optimization is the root of all evil. We only fix what needs fixing, but we fix it right.
Our technologies of choice are Python in the backend and React/Redux in the frontend, and our tech stack includes Django, MySQL, Redshift, S3, DynamoDB, and Elasticsearch storage, asynchronous tasks over RabbitMQ, and distributed data processing over Elastic MapReduce and Spark.
- Masters in Statistics/Machine Learning, or equivalent
- Five or more years of production-level software engineering experience
- Broad knowledge of machine learning models (and their performance characteristics) for classification and regression tasks
- Experience in at least one statistical coding environment (numpy/pandas, R, etc.)
- Fluency in SQL
Nice to have:
- Expertise in causal inference, experiment design, reinforcement learning, and related fields
- Excellent communication of statistical concepts to expert & non-expert audiences
- Specific experience designing and building machine-learning models
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Data is the key to modern marketing. Yet operationalizing all of the data you collect has historically been both labor-intensive and error-prone. Simon changes all of that by eliminating the pain from three of the most friction-laden marketing activities:
- Unifying disparate data sources
- Connecting your data to your marketing channels
- Running rigorous tests and tracking results downstream
Simon does this by sitting between all of your data sources, giving you the ability to create bespoke customer segments using any combination of criteria. Simon then powers smart, automated workflows that connect these segments to all of your marketing channels, all with a built-in suite of testing and reporting tools to help you optimize every aspect of your lifecycle marketing.