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Confido is an AI infrastructure platform serving 200+ CPG brands (including OLIPOP, Simple Mills, Dr. Squatch, and Tropicana) to manage finance, accounting, sales, and operations in a unified system. The company is growing 5x year-over-year with a small team in New York City.
As a Data Analyst, you will build the analytics layer that helps both Confido and its customers understand their financial and operational data. You'll design dashboards, develop core metrics, and surface insights that drive decision-making across the platform. This is a foundational role where you'll help shape Confido's data culture and establish how analytics are delivered internally and to customers.
Key responsibilities include:
- Partner with product, engineering, and customers to understand analytics needs
- Design and build dashboards, reports, and analytical tools for internal and external users
- Write complex SQL queries to analyze large-scale financial and operational datasets
- Define and maintain key business metrics and KPIs
- Identify trends, anomalies, and opportunities within retailer and financial data
- Drive analytical projects from exploration through delivery
- Collaborate with engineers to improve data models and underlying datasets
Example projects include building custom dashboards for brands to understand retailer performance, analyzing deduction and dispute data to identify operational inefficiencies, designing analytics to help brands forecast sales and demand, transforming data into clean analysis-ready datasets, and turning complex financial data into intuitive visual insights.
REQUIREMENTS:
- 2+ years of experience in data analysis or analytics roles
- Advanced SQL skills and experience working with large datasets
- Strong experience building dashboards and analytical reports
- Ability to translate data into clear insights and recommendations
- Strong communication skills working with technical and non-technical stakeholders
Nice to have:
- Experience with BI tools (Omni, Looker, Mode, etc.)
- Experience working with financial, retail, or operational datasets
- Comfort working directly with users
- Interest in early-stage startups and high-ownership roles
- Technical or quantitative degree
