We’re looking for a Lead Product Data Analyst to join our team and help us mature the Analytics function at Jellyfish. You’ll work closely with a wide range of stakeholders to understand business problems across Jellyfish and provide insights, data products and platforms that drive data-informed decision making. Our stakeholders range from product development teams to senior leaders at Jellyfish across both R&D and GTM. The breadth and complexity of available data continues to grow as we integrate with more systems across the business and build more innovative products for our customers. And the tools we’re adding to our data stack will enable us to have an even bigger impact with this new data.
Most importantly, you’ll be part of a highly talented team working in a fun, challenging, and collaborative environment, building a fast-growing business led by experienced entrepreneurs and backed by top-tier investment partners.
Facilitate data-informed decision-making across the product and engineering teams
Partner with product & engineering teams understand important business problems, then own the full lifecycle of data-driven solutions: analysis, metric definitions, transformation pipelines in dbt, experimentation, measurement, data story-telling and, most importantly, influencing decisions
Collaborate with Product, Research, Engineering, Customer Success and others to provide data products allow them to better measure the impact of their work and find new opportunities
Work with data engineers on our team to help build our new Lake House in Databricks in your area of expertise and document vital context about our data that can be used by both stakeholders and AI tools
Provide leadership in how we use product analytics tools like Amplitude to make decisions
Be a key voice in making data-driven decisions in our software development lifecycle
Increase your impact by continuously learning and evolving your workflows as AI technology matures. Form opinions that help Jellyfish support its customers in their AI journeys.
Enable your stakeholders to have a bigger impact through the use of AI in their own analytics workflows. As necessary, build the data tools they need, be their expert-in-the-loop, or influence them to adopt new workflows.
Strong knowledge of SQL (preferably Databricks, Snowflake, or Redshift)
Experience with data quality best practices and building data models in dbt
Experience using Python (numpy, pandas, sklearn, etc.) across exploratory data analysis or predictive modeling
Proven ability to influence and ship with product and engineering teams, especially in B2B SaaS environment
Proven ability to influence product and engineering leaders with data-driven insights
Strong perspective on using the appropriate data solution for the business need at hand
Strong perspective on scaling product analytics solutions, including tools like Amplitude, across a company for both technical and non-technical users
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Growth mindset and flexibility to adapt to changing technology and workflows
A list of job experiences and qualification requirements is great, but humility, a performance-driven attitude, and a team-player approach are most important to us. We love to have fun and win in the process. We only hire people who have a passion for building great companies in an environment where a sense of humor is a must.
Occasional travel may be required.
Applicants must be authorized to work for any employer in the US. We are unable to sponsor or take over sponsorship of an employment visa at this time.
Let’s talk about us!
This is all about you, but you want to know a little about us. Jellyfish enables leaders to effectively build AI-integrated engineering teams, align engineering decisions with business initiatives and deliver the right software efficiently and on time. AI tools alone won’t transform your org—Jellyfish shows you what’s working, what’s not, and how to build high-performing teams that know how to use AI the right way.