Senior Data Scientist at Toast
Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future.
Bready* to make a change?
As a senior data scientist, you will partner across the R&D org and be a critical contributor to the machine learning algorithms using our huge reservoir of point of sale transaction data. You will work with engineers and product managers to turn machine learning models into business impact across product lines, including lending, menu recommendations, and fraud.
About this Roll*:
- Design, build, train and evaluate machine learning models to drive business value for Toast and our restaurant customers
- Write production-level code to convert machine learning models into working production pipelines
- Collaborate closely with fellow data scientists, product, and engineering to frame data science problems and design machine learning solutions
- Work effectively in a dynamic, changing environment while focusing on key goals and objectives
Do you have the right ingredients*?
- Advanced degree in Data Science, Statistics, Applied Math, Computer Science, Engineering or other equivalent quantitative discipline
- Proficiency in Python and SQL; knowledge of some of the following languages, tools, and frameworks: R, Spark, Scala, scikit-learn, Tensorflow, PyTorch, etc. is a plus
- Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration (Airflow, Luigi, etc.) and preferably AWS tooling (Sagemaker, DynamoDB, ECS, etc.)
- Strong knowledge of underlying mathematical foundations of statistics and machine learning
- Experience deploying machine learning models in production environments
- Experience in one or more of the following areas: natural language processing, recommender systems, and deep learning
- Problem solver who loves to dig into different kinds of data and can communicate their findings to cross-functional stakeholders
- Passion for research and curiosity that calls you to go beyond “good enough” to create something innovative and exciting