Data Analyst

The Data Analyst is responsible for analyzing customer data, generating actionable insights, and contributing to improving customer experiences. Engage directly with customers, gather feedback, and use data to drive informed business decisions aimed at enhancing customer satisfaction and organizational success.

The position plays a critical role in presenting company performance to our customers and identifying data anomalies so that we can be proactive in customer retention and success.

• Collect and validate month-end reports.
• Prepare standard reports for leadership, clients, and stakeholders.
• Design and build custom reports and automate recurring reporting.
• Ensure reports are accurate, consistent, and actionable.
• Design and build product reporting and dashboards.
• Support the QBR process with data and content.
• Conduct analysis of assigned customers' performance to identify opportunities for increased loan volume.

• Reconcile customer data against our data. 
• Collect, clean, and analyze customer data using various tools and techniques to identify patterns, trends, and correlations. 
• Interpret data and provide insights to assist in understanding customer behavior, preferences, and needs. 
• Perform root cause analysis on data errors and fix recuring errors.

Customer Engagement and Feedback

• Interact with customer success to gather feedback, understand their requirements, and identify pain points.

Data Visualization and Reporting

• Create visually appealing and easy-to-understand dashboards, reports, and presentations to communicate insights and findings to both internal and external stakeholders. 
• Provide regular updates and insights to the team and management based on the analysis of customer data. 

• Collaborate closely with Data Specialists, Customer Success, Professional Services, and Loan Accounting to ensure customer issues are routed appropriately, resolved efficiently, and communicated clearly.
• Serve as a liaison between customers and internal teams, translating technical or data‑related findings into understandable, actionable explanations.

• Minimum of 2+ years of experience in PowerBI and SQL.
• Bachelor’s degree in Data Science, Statistics, Mathematics, Business Analytics, Computer Science, or a related field.
• Strong analytical skills and proficiency in data analytics tools to interpret complex datasets and identify trends.
• Experience with data modeling and database querying (e.g., SQL, relational databases) for building reliable data structures and reports.
• Experience working with ticketing systems, queues, and structured support workflows.
• Excellent written and verbal communication skills, with the ability to explain data results to non‑technical audiences.
• Proficiency with Microsoft Excel and basic reporting tools.
  

• Always protect company data
• Complete company mandated training regarding security measures to protect company property (e.g. shoulder surfing, phishing attacks, etc.)
• Be aware of all potential threats and surroundings
• Never write down information from your computer monitor
• Do not share any company information unless you have confirmed that person’s identity
• Maintains knowledge of the Bank Secrecy Act (BSA) and the ClearBalance policies that support compliance with BSA
• Performs all duties in a manner that fully supports compliance with all laws and ClearBalance policies

· Own the Outcome: Takes full accountability for results, closes loops, and drives issues through resolution rather than just identifying problems.

· Do the Right Thing: Makes ethical, compliant decisions and speaks up early, even when the easier path would be faster or more convenient.

· Be a Self-Starter: Acts with urgency and initiative, identifies opportunities, and takes action without waiting for direction.

· Be Naturally Curious: Asks why, digs into data and processes, and looks beyond surface-level answers to deliver better outcomes.

· Strive to Make Things Better: Continuously improves processes, reduces friction, and leaves things better than they were found.

· Timely and effective ticket management - Tier 1 support tickets are acknowledged, triaged, and resolved within established SLAs, with minimal aging and clear prioritization.

· High‑quality communication and client experience - Customers and internal teams receive clear, accurate, and timely updates on ticket status, resolution, and next steps.

· Correct escalation and handoff to Tier 2 - Issues requiring reconciliation or advanced investigation are escalated promptly with complete context and documentation, enabling efficient Tier 2 resolution.

· Reduction in repeat and avoidable tickets - Common issues are identified, documented, and addressed through process improvements, resulting in fewer repeat Tier 1 support items.

· Operational reliability and trust - Internal stakeholders and clients view the role as dependable, responsive, and accountable, contributing to stable client relationships and confidence in data support.