Data Analyst I

Job Description

Data Analyst I | Snap Finance

The Tone:
This is a full-time role at Snap Finance, located in West Valley City, UT. Snap Finance is an organization that uses data, machine learning, and a human approach to create flexible financing solutions, helping people move forward regardless of credit history. This role is crucial for leveraging data to drive informed business decisions across the company’s portfolio, contributing to operational efficiency and business performance.

The TL;DR
• Role: Early Career
• Type: Full-time
• Location: In-person, West Valley City, UT

• Mission: Collect, analyze, and interpret data to help drive informed business decisions across Snap’s portfolio.
• Tech Stack: SQL, Python, R, Tableau, R Studio

What You’ll Actually Do
• Data Collection & Analysis: Collect, analyze, and interpret data from multiple sources to support business initiatives and decision-making.
• Reporting & Visualization: Develop and maintain reports, dashboards, and visualizations that provide actionable insights to stakeholders.
• Business Collaboration: Collaborate with business teams to understand reporting requirements and translate them into analytical solutions.
• Data Quality Assurance: Support data validation, quality assurance, and governance efforts to ensure data accuracy and reliability.
• Insight Presentation: Present findings and recommendations to both technical and non-technical audiences.

The Must-Haves
• Background: Bachelor’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Business Analytics, Economics, or a related field.
• Experience: 0–2 years of experience in data analysis, business intelligence, reporting, or related analytical work.
• Skills: SQL, Python, and/or R for querying and analyzing data; understanding of data analysis concepts, statistical methods, and reporting best practices; strong analytical and problem-solving skills; ability to communicate insights clearly to technical and non-technical stakeholders; strong attention to detail and commitment to data accuracy; ability to manage multiple priorities.
• Bonus: AI tool utilization; experience with Python, R, or another analytical programming language; experience building dashboards in Tableau, R, Studio, or Python; exposure to ETL processes, data warehousing, or data modeling concepts; knowledge of statistical analysis, A/B testing, or predictive analytics; experience working with large datasets and complex business problems; internship experience in analytics, finance, technology, or related industries; curiosity for uncovering insights and driving data-informed decision making; experience working in cross-functional team environments; passion for continuous learning and professional development.