Jellyfish

Compensation

Full Description

We’re looking for a Staff 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. Let’s talk about what you'll do: Facilitate data-informed decision-making across the organization Partner with leaders at all levels to understand important business problems, then own the full lifecycle of data-driven solutions: analysis, metric definitions, transformation pipelines in dbt, experimentation, measurement, and data story-telling Collaborate with Product, Research, Customer Success, and Rev Ops 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 and document vital context about our data that can be used by both stakeholders and AI tools 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. Be a leader in data best practices across the Research team and Jellyfish; mentor other team members to help in their growth Let’s talk about what you need to excel: 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 leadership and a track record of shipping improvements with product or GTM teams Proven ability to influence senior decision-makers with data-driven insights Strong perspective on using the appropriate data solution for the business need at hand Strong perspective on scaling analytics solutions 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 Bonus points for experience with: B2B SaaS Start-up environments User interaction data and product usage analytics 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.