Data Scientist II

Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. Toast is revolutionizing the way the restaurant industry does business by pairing technology with an extraordinary commitment to customer success. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, guest-facing technology, and award-winning customer support. Join us as we empower the restaurant community to delight guests, do what they love, and thrive. This role is for a current vacancy. Bready* to make a change? The Toast AI Engineering team is seeking a Data Scientist to embed data science capabilities into the Toast platform by partnering with engineers and product managers to develop statistical and machine learning models that power key product lines. About this Roll* (Responsibilities): Apply a diverse set of expertise including data mining, statistical analysis and machine learning to deliver impactful, objective, and actionable data insights that enable informed business and product decisions Collaborate with cross-functional teams, including sales, marketing, and product, to identify business opportunities and develop data-driven solutions that drive growth and engagement. Partner with line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts Able to effectively communicate analysis, insights and recommendations to high-level business partners in verbal, visual and written formats Thrive in a dynamic and rapidly evolving environment Do you have the right ingredients* (Requirements)? Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred. 2+ years of data science experience in an industry environment. Have solid statistical and machine learning foundations. Familiar with machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation). Experience with advanced machine learning tech niques, including supervised and unsupervised learning, graph algorithms, deep learning (e.g., NLP), recommendation systems, and generative AI. Experience with Python and SQL, and ML frameworks (e.g. scikit-learn, Tensorflow, PyTorch) Experience with cloud solutions, preferably with AWS tooling (e.g. SageMaker, DynamoDB, Athena, Glue, etc.) Experience with model workflow orchestration tool (e.g.