Machine Learning Engineer (Growth)

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 our customer facing upsell motions. You will improve a model-driven recommendation platform to better understand our customers, build lead scoring to drive Sales outreach, and predict and experiment against customer preferences in terms of communication timing and content. Overall you will be improving the long- term value that a customer gets from Gusto by ensuring that they use the products that are most relevant to their business needs and growth.

You’ll be working with an established team and seasoned Growth leaders in Engineering, Product, Design, Data Science, Marketing, and Sales. In this role, you’ll work cross functionally to build Platforms that span the entire breadth of the Growth Stack using machine learning and AI to personalize world class content for our customers and provide timely relevant product recommendations.

Here’s what you’ll do day-to-day:

• Build and deploy models and data products to support internal decision-making, delight our customers, and make our AI solutions even more intelligent.
• Drive research into the problem space, work with stakeholders to understand model requirements, develop the model from scratch, deploy the model alongside your engineering counterparts, and monitor and maintain model performance over time.
• Partner with Engineering, Design, and Product as well as Revenue counterparts in Sales and Customer Success to solve complex cross functional problems.
• Envision and contribute to a robust code base that accelerates machine learning workflows and integrates best practices into our day-to-day operations (including how we partner with AI).
• Learn and build iteratively so we can pressure test opportunities to improve our customers’ experiences and our internal optimization frameworks.
• Knowledge share, mentor, and educate others on where machine learning and AI operate most effectively and what new ways we can drive more impact both within and outside of Gusto.

Here’s what we're looking for:

• We love meeting people with different data backgrounds. For this role, we are looking for at least 7+ years experience building sophisticated and scaled data products with deep domain knowledge of machine learning techniques. This could mean either a MS or PhD in a quantitative field with at least 4 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 7 years of experience working as a data scientist in a business setting.
• Experience developing and deploying modeling solutions in production code using Python such as propensity scoring, recommendation engines, and forecasting. A background in growth-oriented product development will accelerate the impact you can generate.
• Strong programming skills - comfortable with all phases of the machine learning lifecycle, from initial analysis and model prototyping all the way through to monitoring and retraining.
• 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 leveraging customer feedback, chat transcripts, and LLMs as both inputs to the model and to generate outputs from a model is a plus

Our cash compensation amount for this role is targeted at $165-205k in Denver, $200-250k for San Francisco, New York, and Seattle, and $185k-225k CAD for Toronto. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.