Asks for

The ad says“Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.”
The ad says“Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Experience with distributed data processing and training, real-time inference, and ML Ops frameworks”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Experience building services on top of LLMs in a large scale production environment.”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Experience with distributed data processing and training, real-time inference, and ML Ops frameworks”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).”
The ad says“Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).”
The ad says“Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.”
The ad says“Experience with distributed data processing and training, real-time inference, and ML Ops frameworks”
The ad says“Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.”
The ad says“Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).”
The ad says“Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.”
The ad says“Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.”
The ad says“Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.”

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.

A day in the life (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.

What you'll need to thrive (Requirements)

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.

Bonus ingredients*:

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.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

#LI-Remote

The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy.

Zone A

$170,000—$272,000 USD

Zone B

$148,000—$237,000 USD

Zone C

$133,000—$213,000 USD

How Toast Uses AI in its Hiring Process

Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. We ask that you complete interviews and assessments on your own, without real-time AI tools, recording, or transcription bots, unless we tell you otherwise in advance. To learn more: https://careers.toasttab.com/ai-in-hiring

Our Approach to Hybrid Working

We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast

People Are the Secret Ingredient in Our Recipe for Success

At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry brings together people with a wide range of backgrounds, experiences, and perspectives, and we value that same breadth at Toast. We strive to build a culture grounded in authenticity, respect, and humility, where every Toaster has a real opportunity to grow, contribute, and do their best work—raising the bar in delivering exceptional experiences for our customers and each other.

Apply today!

Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com.

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For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Asks for

Values