Principal 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 Principal Data Scientist, you will partner across the R&D org and represent the team as the technical thought leader and contribute to building machine learning algorithms using our huge reservoir of point of sale transaction data. You will work with architects, engineers and product managers to turn machine learning models into business impact across product lines, including lending, menu recommendations, and fraud.
About this Roll*:
- Lead the team to design, build, train and evaluate machine learning models to drive business value for Toast and our restaurant customers
- Collaborate closely with internal and external product stakeholders, both technical and non-technical and help translate deep machine learning knowledge to product applications
- Work closely with ML engineering and platform team to help define the vision of Machine Learning training and inference platforms running on the cloud
- Break down larger ML initiatives into smaller problems that enables data science to deliver incremental business value and lead the team to execute on them
- Mentor and grow other data scientists and engineers in the team on both data science modeling and software engineering skills
- Incorporate up-to-date ML technology and DS approach as best practice for the team
- Help in continuing to build out and expand the Data Science and ML Engineering teams
- 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
- 7+ years of industry experience in the field of Data Science and Machine Learning
- Strong proficiency in Python and SQL; experience with some of the following languages, tools, and frameworks: R, Spark, Scala, scikit-learn, Tensorflow, PyTorch, etc.
- 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
- Prior success deploying machine learning solutions in large-scale production environments
- Deep experience in one or more of the following areas: natural language processing, recommender systems, and deep learning
- Experience collaborating with cross-functional teams and stakeholders to evaluate new Machine Learning opportunities
- 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