Gusto
Staff Machine Learning Modeler, Payments & Risk
Gusto, San Francisco, California, United States, 94199
Staff Machine Learning Modeler, Payments & Risk
About Gusto Gusto is a modern, online people platform that helps small businesses take care of their teams. On top of full-service payroll, Gusto offers health insurance, 401(k)s, expert HR, and team management tools. Today, Gusto offices in Denver, San Francisco, and New York serve more than 400,000 businesses nationwide. Our mission is to create a world where work empowers a better life, and it starts right here at Gusto. That’s why we’re committed to building a collaborative and inclusive workplace, both physically and virtually. Learn more about our Total Rewards philosophy. About the Role: Gusto’s Data Science team leverages Gusto’s rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers. For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem. You’ll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world-class, high secure platform that safeguards our users’ activities and money, and ensures unparalleled reliability. Here’s what you’ll do day-to-day:
Build and deploy machine learning models to identify, assess and mitigate risks Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights Identify new opportunities to leverage data to improve Gusto’s products and help risk management team to understand business requirements and develop tailored solutions Present and communicate results to stakeholders across the company Here’s what we're looking for:
8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, XGBoost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion PhD or Masters plus equivalent experience in a quantitative field is a plus Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $170,000 - $205,000 in Denver, $185,000- $225,000 in Los Angeles, $220,000 - $270,000 for San Francisco, New York, and Seattle, and $185,000 - $225,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Voluntary Self-Identification
Our customers come from all walks of life and so do we. We hire people from a wide variety of backgrounds, not just because it’s the right thing to do, but because it helps us to build better products, better serve our customers, and makes our company stronger. In addition to the information required to consider your application, below is a set of demographic questions that help us identify areas for improvement in our process and further support the development and execution of our diversity efforts and programs as well as to create a more inclusive environment for all employees. Your responses to these questions will be recorded and maintained in a confidential file. Your responses, or your wish not to answer, will not be associated with your specific application, will not be shared with hiring managers, and will not in any way be used in making any employment decisions, including hiring decisions.
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About Gusto Gusto is a modern, online people platform that helps small businesses take care of their teams. On top of full-service payroll, Gusto offers health insurance, 401(k)s, expert HR, and team management tools. Today, Gusto offices in Denver, San Francisco, and New York serve more than 400,000 businesses nationwide. Our mission is to create a world where work empowers a better life, and it starts right here at Gusto. That’s why we’re committed to building a collaborative and inclusive workplace, both physically and virtually. Learn more about our Total Rewards philosophy. About the Role: Gusto’s Data Science team leverages Gusto’s rich dataset to guide product direction and decision-making. We operate full-stack, conducting analyses, prototyping and deploying predictive models and statistical tools both for internal use and for our customers. For this role, we are looking for a technical leader (an individual contributor) to drive machine learning and AI in the payment and risk domains. You will build a model-driven risk platform to provide a trusted environment for Gusto Ecosystem. You’ll be working with an established team and seasoned payments and risk leaders in Engineering, Product, Design, Operation, Identity and Compliance. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Payments and Risk Stacks, and use ML and AI to build a world-class, high secure platform that safeguards our users’ activities and money, and ensures unparalleled reliability. Here’s what you’ll do day-to-day:
Build and deploy machine learning models to identify, assess and mitigate risks Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights Identify new opportunities to leverage data to improve Gusto’s products and help risk management team to understand business requirements and develop tailored solutions Present and communicate results to stakeholders across the company Here’s what we're looking for:
8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting. Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, XGBoost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models. Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications. Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion PhD or Masters plus equivalent experience in a quantitative field is a plus Experience in the Fintech industry is a plus Our cash compensation amount for this role is targeted at $170,000 - $205,000 in Denver, $185,000- $225,000 in Los Angeles, $220,000 - $270,000 for San Francisco, New York, and Seattle, and $185,000 - $225,000 CAD for Toronto, Canada. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above. Gusto has physical office spaces in Denver, San Francisco, and New York City. Employees who are based in those locations will be expected to work from the office on designated days approximately 2-3 days per week (or more depending on role). The same office expectations apply to all Symmetry roles, Gusto's subsidiary, whose physical office is in Scottsdale. Note: The San Francisco office expectations encompass both the San Francisco and San Jose metro areas. When approved to work from a location other than a Gusto office, a secure, reliable, and consistent internet connection is required. This includes non-office days for hybrid employees. Gusto is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristic. Gusto considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Gusto is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. We want to see our candidates perform to the best of their ability. If you require a medical or religious accommodation at any time throughout your candidate journey, please fill out this form and a member of our team will get in touch with you. Voluntary Self-Identification
Our customers come from all walks of life and so do we. We hire people from a wide variety of backgrounds, not just because it’s the right thing to do, but because it helps us to build better products, better serve our customers, and makes our company stronger. In addition to the information required to consider your application, below is a set of demographic questions that help us identify areas for improvement in our process and further support the development and execution of our diversity efforts and programs as well as to create a more inclusive environment for all employees. Your responses to these questions will be recorded and maintained in a confidential file. Your responses, or your wish not to answer, will not be associated with your specific application, will not be shared with hiring managers, and will not in any way be used in making any employment decisions, including hiring decisions.
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