Note: The job is a remote job and is open to candidates in USA. Toast creates technology to help restaurants and local businesses succeed in a digital world. As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for various use cases while serving as a technical thought partner across teams.
Responsibilities
- Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives
- Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights
- Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy
- Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization
- Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise
- Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward
- Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team
Skills
- 7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact
- Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation
- Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions
- Experience with distributed data processing and training, real-time inference, and ML Ops frameworks
- Prior experience mentoring other data scientists or acting as a tech lead
- Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems
- Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)
- Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD
- Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock
- Excellent communication skills and the ability to influence both technical and non-technical stakeholders
- Strong business acumen with the ability to align technical solutions with company goals
- Experience building services on top of LLMs in a large scale production environment
- An advanced degree in Computer Science, Statistics, or a related STEM field is preferred
- Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability
- Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment
Benefits
- Cash compensation (overtime, bonus/commissions if eligible)
- Equity
- Benefits
- Hybrid work model that fosters in-person collaboration while valuing individual needs
- Reasonable accommodations for persons with disabilities to enable them to access the hiring process
Company Overview
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