Data Scientist II

Toast

Data Scientist II developing statistical and machine learning models for Toast’s restaurant technology platform. Delivering actionable insights and AI capabilities through collaboration with product and engineering teams.

Posted 8/7/2026full-time🇺🇸 United StatesJuniorMid-Level💰 $87,000 - $179,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data mining, statistical analysis, and machine learning to drive business insights and product decisions. Proficient in collaborating with cross-functional teams and communicating complex analyses effectively to stakeholders.

Highest-signal resume keywords

Data Science ExperienceStatistical AnalysisMachine Learning FoundationsPython ProgrammingCloud Solutions (AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data MiningStatistical AnalysisMachine LearningRegression/ClassificationClusteringSupervised LearningUnsupervised LearningGraph AlgorithmsDeep LearningNatural Language Processing

Soft Skills

Excellent Communication SkillsCollaboration

Tools & Technologies

PythonSQLScikit-LearnTensorFlowPyTorchAWS SageMakerDynamoDBAthenaGlueAirflow

Industry Keywords

Data-Driven SolutionsModel EvaluationRecommendation SystemsGenerative AIA/B TestingExperimentation Methodologies

Tech Stack

Tools & technologies

AirflowAWSCloudDynamoDBPythonPyTorchScikit-LearnShell ScriptingSQLTensorflow

About the role

Key responsibilities & impact

Apply data mining, statistical analysis, and machine learning to deliver actionable insights for business and product decisions
Collaborate with sales, marketing, product, engineers, and data scientists to identify opportunities and develop data-driven solutions
Partner with line-of-business teams to foster impactful data-driven decisions
Communicate analyses, insights, and recommendations to senior business partners in verbal, visual, and written formats
Develop statistical and machine learning models powering key Toast product lines
Work effectively in a dynamic, rapidly evolving environment

Requirements

What you’ll need

Bachelor’s degree in computer science, engineering, math, statistics, economics, or another quantitative discipline; master’s preferred
2+ years of data science experience in an industry environment
Solid statistical and machine learning foundations
Familiarity with regression/classification, clustering, and offline/online model evaluation
Experience with supervised and unsupervised learning, graph algorithms, deep learning/NLP, recommendation systems, and generative AI
Experience with Python, SQL, and ML frameworks such as scikit-learn, TensorFlow, and PyTorch
Experience with cloud solutions, preferably AWS tooling such as SageMaker, DynamoDB, Athena, and Glue
Experience with model workflow orchestration tools such as Airflow
Experience collaborating with engineers, product managers, and cross-functional teams
Excellent verbal and written communication skills
Ability to communicate sophisticated quantitative analysis clearly, precisely, and actionably
Nice-to-have: LLM applications, prompting, RAG, and evaluation
Nice-to-have: software engineering best practices including object-oriented programming, test-driven development, CI/CD, Git, shell scripting, and task orchestration
Nice-to-have: shipping machine learning systems in production
Nice-to-have: A/B testing and experimentation methodologies

Benefits

Comp & perks

Competitive compensation and benefits programs
Cash compensation, including overtime and bonus/commissions if eligible
Equity
Flexible benefits supporting a healthy lifestyle and changing needs
AI tools provided across disciplines to support work
Reasonable accommodations during the hiring process