Senior Data Scientist, Toast

• Thrive in a fast-paced environment with a strong ownership mindset and a bias toward iteration and learning
• 3+ years of experience in data science, with strong foundations in statistical analysis and machine learning
• Proven experience independently driving ML projects end-to-end—from data wrangling and modeling to deployment and monitoring
• Strong experience with regression, classification, time series, clustering, and model evaluation techniques
• Familiarity in LLMs, and their applications in real-world systems
• Proficient in Python, SQL, and commonly used ML libraries (e.g., scikit-learn, PyTorch, TensorFlow)
• Experience with cloud platforms and tools, especially AWS (e.g., SageMaker, Athena, DynamoDB, Glue, Bedrock)
• Working knowledge of software engineering best practices, including object-oriented programming, testing, CI/CD, and version control
• Strong communication skills, with the ability to align technical solutions with business impact and explain complex ideas to diverse audiences

Desirable

• We’re looking for a Senior Data Scientist to drive machine learning and statistical modeling across a wide range of applications, including menu and offer recommendation, time series forecasting, and customer personalization
• You’ll work at the intersection of data, product, and engineering to design, build, and deploy scalable ML solutions that directly impact our customers
• Apply advanced techniques in data mining, statistical modeling, and machine learning to solve real-world business problems and influence strategic decisions
• Lead development of production-grade ML models and partner closely with MLEs to ensure scalable, robust deployment
• Collaborate with cross-functional teams across sales, marketing, product, and engineering to identify opportunities and deliver data-driven solutions that improve customer experience and drive growth
• Design, monitor, and evaluate model performance using rigorous offline and online testing methods
• Translate complex quantitative insights into clear, actionable recommendations for technical and non-technical stakeholders