Data Analyst

Vertical Insure•Minneapolis, MN

2d•$75,000 - $110,000

About The Position

Data drives everything we do, from improving the customer experience to helping our partners grow and making smarter business decisions. As our Data Analyst, you'll transform complex data into actionable insights that influence strategy across Product, Sales, Customer Success, Finance, and Leadership. You'll help us understand what's working, identify opportunities for growth, and build the reporting infrastructure that enables us to scale. This is an excellent opportunity for someone who enjoys wearing multiple hats, working with a variety of data sources, and helping build a data-driven culture.

Requirements

Bachelor's degree in Data Analytics, Statistics, Mathematics, Computer Science, Economics, or a related field.
3+ years of experience in a Data Analyst or Business Analyst role.
Strong SQL skills and experience with data visualization tools.
Experience with BI tools such as Tableau, Power BI, or similar.
Advanced Excel or Google Sheets skills.
Experience analyzing large datasets and communicating findings to non-technical audiences.
Strong analytical thinking and problem-solving skills.
Excellent communication and presentation skills.
Ability to manage multiple priorities in a fast-paced environment.

Nice To Haves

Experience with product analytics tools.
Background in fintech, insurance, or vertical SaaS industries.

Responsibilities

Develop and maintain dashboards, reports, and KPIs for business leaders.
Analyze customer, product, revenue, and operational data to identify trends and opportunities.
Partner with Product, Sales, Customer Success, Finance, and Leadership to answer key business questions.
Translate data into clear recommendations that drive business decisions.
Monitor business performance and proactively identify risks or opportunities.
Build and optimize complex SQL queries to extract data from various sources for deep-dive analysis.
Ensure data accuracy and consistency across reporting systems.
Support forecasting, planning, and executive reporting.
Assist in developing data definitions, documentation, and reporting standards.
Identify opportunities to automate reporting and improve processes.