|Gusto (formerly ZenPayroll)|
|Senior Data Scientist|
Gusto is looking for an experienced data scientist skilled at building and deploying predictive models and performing deep statistical analyses to support and accelerate our growth initiatives.
In this role you will partner with our Marketing, Sales and Growth Product teams to build and deploy models and conduct analyses that enable Gusto to grow faster and more efficiently. As a core member of a new and impactful team, you will also be a core contributor to building our data science practice from the ground up!
The Data Science team leverages Gusto’s data to deliver data-informed insights for our customers and inform 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.
Here’s what you’ll do day-to-day:
Build and deploy models that can be used for forecasting and optimization, in areas such as:
Predicting lead and customer value (conversion, churn, growth, etc.)
Targeting upsell of additional products and product tiers both in-app and through marketing and sales efforts
Helping our product fulfillment teams onboard new customers faster and more efficiently
Develop reusable statistical tools for tracking and analyzing growth experiments
Conduct ad hoc statistical analyses and deep dives into our data to support Gusto’s growth and better understand the small businesses we serve
Enhance and contribute to the team’s core analysis and modeling systems and libraries
Present and communicate results across the company
Identify new opportunities to leverage data to improve Gusto’s products and help our business
Here’s what we’re looking for:
At least 5 years experience conducting statistical analyses on large datasets, ideally in a business context (can supplement with academic experience where appropriate)
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 - generalized linear modeling, regularization, ensemble models (e.g., random forest, gradient boosting), Bayesian analysis methods
Strong programming skills - comfortable with all phases of the data science development process, from initial analysis all the way through 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
Experience designing valid controlled experiments and conducting robust analyses on the resulting data is a plus