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.
Bready* to make a change?
Toast is looking for a Staff Data Scientist to bring data science capabilities into the Toast platform. You will work with engineers and product managers to build statistical and machine learning models for product lines, such as sales recommendation and Toast product package recommendation.
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 line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts
- Monitor and analyze the performance of existing models and strategies, identifying areas for improvement and implementing data-driven refinements as needed.
- Present complex data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner, while fostering a data-driven culture within the organization.
- Mentor and guide junior data scientists, fostering a collaborative environment and promoting the growth and development of the AI Engineering team.
- Stay current with the latest trends and developments in data science and AI, continually exploring new methods and technologies to enhance the organization's capabilities.
- Thrive in a dynamic and rapidly evolving environment
Do you have the right ingredients*? (Requirements)
- Advanced degree in quantitative field such as Data Science, Statistics, Mathematics, Financial Engineering or related discipline
- 7-10 years of data science, machine learning and NLP experience
- Proficiency in machine learning, AI, and statistical modeling techniques (e.g. regression , with a strong track record of developing and deploying successful predictive models in a scalable production setting.
- Strong proficiency in Python and SQL and experience with data science libraries and tools such as: Spark, Scala, scikit-learn, Tensorflow, PyTorch, XGBoost etc.
- Experience with cloud solutions, preferably with AWS tooling (e.g. SageMaker, DynamoDB, Athena, Glue, etc.)
- Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, task orchestration (Airflow) and AWS tooling
- Excellent communication and presentation skills, with the ability to articulate complex data-driven insights to both technical and non-technical stakeholders.
- Strong leadership skills, with experience mentoring and guiding junior data scientists
Bonus ingredients*:
- Passion for research and curiosity that calls you to go beyond “good enough” to create something innovative and exciting
- Self starter who loves to dig into different kinds of data to solve business problems and can communicate their findings to cross-functional stakeholders
- Experience with LLM and building GenAI applications in production is a plus
Our Spread* of Total Rewards
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.
*Bread puns encouraged but not required
The base salary range for this role is listed below. The starting salary will be determined based on skills and experience. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits.
Pay Range
$143,000—$229,000 USD
Diversity, Equity, and Inclusion is Baked into our Recipe for Success
At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences.
We Thrive Together
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 restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast.
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 [email protected].
Top Skills
What the Team is Saying
What We Do
Toast is the all-in-one platform built for restaurants of all sizes. Toast provides a single platform of software as a service (SaaS) products and financial technology solutions that give restaurants everything they need to run their business, including point of sale, payments, supplier management, digital ordering and delivery, marketing and loyalty, and team management. By serving as the restaurant operating system across dine-in, takeout, and delivery channels, Toast helps restaurants increase revenue, streamline operations and deliver amazing guest experiences.
Why Work With Us
Our recipe for an awesome workplace:
One splash of friendship
A dollop of impact
A sprinkle of no hierarchy &
A heavy spoonful of individuality
Mix these ingredients in a fast-paced and hardworking environment. Best paired with a side of interesting people who always bring their whole selves to work.
*100% Sunday scary free
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Toast Teams
Toast Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
