This role pays less than
55%
of similar roles. Most pay
$126,800–$169,087
— the shaded band above.
At the midpoint, this role pays about
$146k
versus about
$148k
for comparable roles.
Based on 240 similar postings.
Employer
About Toast, Inc.
Toast is a cloud-based restaurant management platform providing point-of-sale, payment processing, and operations software for the food service industry.
Toast, Inc. currently has
29 open roles
on FindRole.
Listed pay typically runs
$190,000–$304,000
across 29 roles with salary data.
The Data Scientist II joins the AI Engineering team to embed data science capabilities into the Toast platform by partnering with engineers and product managers. This role involves developing statistical and machine learning models that power key product lines while providing actionable insights for business and product decisions. The successful candidate will utilize a diverse set of expertise including data mining, statistical analysis, and advanced machine learning techniques such as supervised/unsupervised learning, graph algorithms, deep learning, recommendation systems, and generative AI. Required technical skills include Python, SQL, and ML frameworks like scikit-learn, TensorFlow, or PyTorch, alongside experience with AWS tools, Airflow, and LLM applications. The role focuses on solving problems within the restaurant industry by creating data-driven solutions to improve operations, increase revenue, and enhance guest experiences through integrated point of sale technology.
What does a Data Scientist earn in Remote?
Median $217225 from 40 postings across 18 companies.
Develop statistical and machine learning models to power key product lines within the Toast platform.
Apply data mining and statistical analysis to deliver actionable insights for business and product decisions.
Identify business opportunities and develop data-driven solutions to drive growth and engagement.
Communicate complex quantitative analysis and recommendations to high-level business partners in various formats.
Build and implement advanced machine learning techniques including supervised/unsupervised learning, NLP, and recommendation systems.
Utilize Python, SQL, and ML frameworks like TensorFlow or PyTorch to develop production-ready models.
Manage model workflows and data pipelines using tools such as Airflow and AWS services.
Execute A/B testing and experimentation methodologies to measure the effectiveness of product launches.
What we're looking for
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 foundations in statistical analysis and machine learning concepts like regression, classification, clustering, and model evaluation.
Experience with advanced machine learning techniques including supervised/unsupervised learning, graph algorithms, deep learning (NLP), recommendation systems, and generative AI.
Proficiency in Python, SQL, and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
Experience with cloud solutions, preferably using AWS tools like SageMaker, DynamoDB, Athena, and Glue.
Experience with model workflow orchestration tools such as Airflow.
Excellent verbal and written communication skills to convey complex quantitative analysis to business partners.
Python
R
SQL
Generative AI
Agentic AI
Prompt Engineering
RAG
Machine Learning
Pandas
NumPy
Scikit-learn
TensorFlow
PyTorch
Tableau
Power BI
Data Warehousing
Statistics
Feature Engineering