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Gusto

Runs payroll and HR software for small businesses

Staff Machine Learning Engineer - Risk

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 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 may be satisfied by an MS or PhD in a quantitative field plus at least 5 years of experience in a business environment, or by a BS or Data Science Bootcamp graduate plus at least 8 years of experience as a data scientist or 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 statistical and modeling techniques using Python, R, or another statistical modeling language, including predictive modeling, anomaly detection, and ensemble methods; natural language processing is optional. Basic understanding of LLMs and their applications is required.
  • Strong programming skills and comfort with all phases of the data science development process, from initial analysis and model development to deployment.
  • Ability to communicate findings and recommendations clearly to non-technical stakeholders.

Responsibilities

  • Build and deploy machine learning models to identify, assess, and mitigate risks.
  • Drive research in the problem space, work with stakeholders to understand model requirements, develop models from scratch, deploy them with engineering counterparts, and monitor and maintain model performance over time.
  • Partner with Engineering, Design, and Product counterparts in Identity and Risk to solve complex cross-functional problems.
  • Develop scalable frameworks and libraries that enhance the team's core analysis and modeling capabilities, including integrating LLMs to improve data processing, analysis, and insights.
  • Identify opportunities to leverage data to improve Gusto's products, and help the risk management team understand business requirements and develop tailored solutions.
  • Present and communicate results to stakeholders across the company.

Desired Qualifications

  • A PhD or Master's degree in a quantitative field, plus equivalent experience.
  • Experience in the FinTech industry.

About the Company

Gusto

Runs payroll and HR software for small businesses

Gusto runs payroll, benefits administration, and HR software for small and midsize businesses that want to manage their teams in one place. Its payroll system calculates wages and taxes, files required forms, and connects employee hours with pay runs. Employers use the same platform to enroll workers in health insurance and retirement plans, manage time off, and organize hiring paperwork, while staff access paystubs through personal accounts. Businesses pay monthly subscription fees based on their plan and workforce size, with extra charges for selected services and faster payment options. Gusto was founded in 2011 and is headquartered in San Francisco, California.

Company size
1,001-5,000
Company stage
Series E
Total funding
$706.2M
Headquarters
San Francisco, CA
Founded
2011

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