Sr. Data Analyst

Overview

GRIN is seeking a Sr. Data Analyst to unlock insights and metrics as we drive growth across the organization. They will own data analysis and develop a strategy to convert information into a digestible format for your stakeholders, both internal and external. The Sr. Data Analyst will significantly impact the organization, from acquisition to retention, by collaborating across all company teams.

Data-driven transformation through democratized access to data empowers our teams to make smarter decisions and adapt quickly, leading to significant efficiency gains, growth in core metrics, and improved morale. As we integrate cutting-edge technologies in data infrastructure, AI, AR/VR, and machine learning, we anticipate rapid growth and exciting opportunities in a dynamic, high-growth environment.

Responsibilities:

• Use a variety of data analysis tools to explore our existing dataset, uncover correlations, predictive metrics, and other insights that drive growth.
• Build, own, and manage initiatives to develop and automate tooling, dashboards, and training to communicate relevant growth metrics to stakeholders, both regularly and on an ad-hoc basis.
• Assist other team members in data analysis to explore and validate hypotheses.
• Collaborate with engineering to shape and drive the development of data infrastructure, reporting, and analytical applications, including building ETL pipelines.
• Proactively initiate, scope, and execute projects with minimal guidance, working closely with multiple teams to understand business requirements and ensure solutions fit evolving needs.
• Deliver reporting and analytics to cross-functional management teams, including generating automated weekly reporting and dashboards on various KPIs, and performing ad-hoc analysis on metrics such as CPA, CAC, LTV, and ROI.
• Present insights and recommendations from analyses to leadership to influence decisions and direction across the company.
• Develop, maintain, and improve relationships with internal business leaders and external vendors and partners.

Qualifications:

• 6+ years analytical experience with high data volume environments, preferably in a SaaS environment.
• Technical expertise regarding statistics, data models, database design development, data mining and segmentation techniques.
• Demonstrated experience in data standards or processes and data governance 
• Demonstrated experience in experimental design & interpretation, exploratory data analysis & prototyping. Startup experience is a plus.
• Strong database experience including ability to perform complex  SQL queries and API integrations.
• Python programming: ability to write code, explain code, teach others about the code; perform ad-hoc exploratory data analysis using Jupyter notebooks
• Working knowledge of Tableau, Databricks, Hive, NoSQL, Hadoop, Graph or other BI/data applications and related languages.
• Ability to clearly articulate complex data concepts and customize communications for diverse audiences, while educating, persuading, and training others to leverage data to influence behavioral change and improve core KPIs across departments.