Staff Decision Scientist

We're looking for a Staff Decision Scientist to join the Insights Foundations team inside of Decision Science & Analytics at Zapier.

Decision Science & Analytics is responsible for driving data insights, experimentation and quantitative research at Zapier. We work across Product & Revenue, Marketing, Finance, Engineering and Customer Support, steering our business stakeholders to take data-informed decisions and deepening business understanding of opportunities and weaknesses.

Insights Foundations is responsible for catalyzing and empowering a vibrant and powerful insights community through common research, tooling, processes, and institutions.

As a Decision Scientist in Insights Foundations you’ll engage with and help folks across the entire insights spectrum from Data Engineering to UX Research. In this role you also will develop tight-knit thought partnerships with and provide data insights for our Engineering team. If you are a curious Decision Scientist interested in helping to grow a product that helps the world automate their work so they can get back to living, this may be the right challenge for you!

We know applying for and taking on a new job at any company requires a leap of faith. We want you to feel comfortable and excited to apply at Zapier. To help share a bit more about life at Zapier, here are a few resources in addition to the job description that can give you an inside look at what life is like at Zapier. Hopefully, you'll take a leap of faith and apply.

Zapier is proud to be an equal opportunity workplace dedicated to pursuing and hiring a diverse workforce.

About You

You are a skilled oral and written communicator. Zapier is a 100% remote team and writing is our primary means of communication. This is especially important in Insights Foundations as you’ll regularly need to communicate complex technical issues clearly and approachably across a wide variety of reader skill levels.

You have proven stakeholder management expertise. As a collaborative and empathetic thought partner you're able to clearly express your findings to a technical audience whose skill set differs substantially from your own, and you’re comfortable with operating with a high degree of autonomy to proactively shape your roadmap. It is especially valuable if you’ve either been or have worked closely with software engineers in the past.

You have extensive experience in conducting statistical analyses or machine learning approaches to explore and understand loosely defined problems to discover actionable solutions. You are a veteran (8+ years of experience) in designing experiments and application of associated statistical methods (e.g. generalised linear models, significance testing, confidence/credible intervals, and the interpretation of coefficients) and one or more complex statistical or machine learning techniques (e.g. multilevel models, survival analysis, hyperdimensional language models, random forests, CART, mediation/moderation analyses, structural equation modeling, time series modelling, or classification/clustering techniques). In particular, you thrive on helping others learn to use these techniques as well as leveraging them to systematically enhance our understanding of the problem space.

When it comes to Python and/or R, you’ve mastered one data visualization tool and are a function and package builder. Code you write has been used and reused by others and you enjoy building it.

You have a basic understanding of DevOps/SRE and are able to build and deploy statistical solutions in a cloud environment.

You enjoy collaboration and knowledge sharing. You appreciate our team’s values of eagerness to collaborate with teammates with any level of statistical knowledge, iterating over your deliverables, and being curious.

You understand that perfect is the enemy of good and that the good is the enemy of the great. You will default to action by initially shipping solutions that simply work and work simply, while iterating as needed to meet the needed level of quality.

Things You Might Do

Zapier is a fast-growing and remote-first company, and Insights Foundations is a cross-cutting central function in Decision Science. So, you’ll get to contribute to many different projects across all of Zapier! Here are some things you might get to help our teams with:

Develop and maintain tools and processes that catalyze productivity across insights functions at Zapier, e.g. R and Python packages, including testing & CI, to support common analysis tasks
Serve as the Zapier expert for one or more quantitative methods
Identify and conduct or guide additional quantitative and/or qualitative research to enhance Zapier’s understanding of our customers and key business processes
Write practical review articles that summarize existing internal and external quantitative and qualitative research
Summarize elements/areas of your expertise and adjacent to your expertise for a diverse audience with multiple skill levels in a way that is accessible and relevant to Zapier, e.g. a document on the impact of multiple comparisons on decision making when using null hypothesis tests
Conduct trainings and guide others in developing skills in your areas of expertise
Host Town Square meetings for all data/insights functions to solve problems and cross pollinate understanding
Structure and coordinate a system of peer review
Identify opportunities where the addition of particular methods can catalyze value for the organization
The tools you’ll use include Python or R, RStudio Server Pro, AWS (especially Redshift, Redshift Spectrum, EC2, Route 53, & EKS), Apache Airflow, SQL.
Help engineering teams evaluate their current data, and collect more data, to identify system issues before they substantively affect the experience of our users.
As a part of Zapier's all-hands philosophy, help customers via support to ensure they have the best experience possible.

How To Apply

We have a non-standard application process. To jump-start the process we ask a few questions we normally would ask at the start of an interview. This helps speed up the process and lets us get to know you a bit better right out of the gate. Please make sure to answer each question.

After you apply, you are going to hear back from us, even if we don't seem like a good fit. In fact, throughout the process, we strive to make sure you never go more than seven days without hearing from us.