Data Scientist II

Toast

3d • $87,000 - $179,000 • Hybrid

About The Position

Toast’s AI Engineering team is seeking a Data Scientist to embed data science capabilities into the Toast platform. The role partners with engineers and product managers to develop statistical and machine learning models that power key product lines. The Data Scientist applies data mining, statistical analysis, and machine learning to produce impactful, objective, actionable insights that support business and product decisions. The role collaborates with business and cross-functional partners to identify opportunities and develop data-driven solutions that drive growth and engagement, and communicates analysis and recommendations to senior business partners. Toast describes its culture as dynamic and rapidly evolving, with an emphasis on learning and adopting AI tools to build for customers. The position follows a hybrid work model intended to foster in-person collaboration while valuing individual needs; in-office expectations vary by region. Compensation includes base salary, and may also include overtime, bonus or commissions if eligible, equity, and benefits. Base salary ranges by geographic zone are $112,000–$179,000 in Zone A, $97,000–$155,000 in Zone B, and $87,000–$139,000 in Zone C. Starting salary depends on skills, experience, and geographic location.

Requirements

• Bachelor’s degree in computer science, engineering, mathematics, statistics, economics, or another quantitative discipline; a master’s degree is preferred.
• At least 2 years of data science experience in an industry environment.
• Solid foundations in statistics and machine learning, including familiarity with regression, classification, clustering, and offline/online model evaluation.
• Experience with advanced machine learning techniques, including supervised and unsupervised learning, graph algorithms, deep learning such as NLP, recommendation systems, and generative AI.
• Experience with Python, SQL, and machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Experience with cloud solutions; AWS tooling such as SageMaker, DynamoDB, Athena, and Glue is preferred.
• Experience with a model workflow orchestration tool such as Airflow.
• Experience collaborating with engineers, product managers, and other cross-functional teams.
• Excellent verbal and written communication skills.
• Ability to communicate sophisticated quantitative analysis clearly, precisely, and in an actionable manner.

Nice To Haves

• Experience with LLM applications, including prompting, retrieval-augmented generation (RAG), and evaluation.
• Experience with software engineering best practices and tools, including object-oriented programming, test-driven development, CI/CD, Git, shell scripting, and task orchestration.
• Experience shipping machine learning systems in production environments.
• Experience with A/B testing and other experimentation methodologies for measuring product launches.

Responsibilities

• Apply data mining, statistical analysis, and machine learning to deliver impactful, objective, actionable insights for business and product decisions.
• Collaborate with sales, marketing, product, and other cross-functional teams to identify business opportunities and develop data-driven solutions that drive growth and engagement.
• Partner with line-of-business teams, product managers, engineers, and data scientists to foster data-driven decisions with significant impact.
• Communicate analysis, insights, and recommendations to high-level business partners through verbal, visual, and written formats.
• Work effectively in a dynamic and rapidly evolving environment.

Benefits

• Competitive compensation and benefits programs.
• Equity.
• Cash compensation, including overtime and bonus or commissions if eligible.
• Benefits intended to support a healthy lifestyle and flexibility for changing needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level