Field Examination- Data & Analytics-Analyst

Asset Based Lending (ABL) is a form of financing that provides asset-based loans to a wide range of companies particularly those with asset-rich balance sheets and working capital needs. ABL supports businesses across diverse industries such as Consumer & Retail Industrials Metals & Mining Oil & Gas and Tech/Media/Telecom etc. ABL offers full-service solutions including originations syndications portfolio management collateral monitoring and loan servicing for both syndicated and sole-lender transactions.

As a Field Exam Data & Analytics Analyst in Risk Management and Compliance you will be dedicated to standardizing processes automating workflows and leveraging AI and automation capabilities (e.g. automated data ingestion from disparate sources AI-assisted workpaper review etc.) to achieve measurable results for clients and internal stakeholders.

The role of an ABL Field Exam Analyst Data & Analytics focuses on generating structured data capture trend analyses and operational reporting inputs that enable centralized insights and improved risk identification. The team foster. s an environment that values intellectual curiosity critical thinking and a passion for enabling analytics-driven decision making.

You will be a founding member of the Field Exam D&A team responsible for assisting in the design and development of the data model building centralized data storage and creating the AI-augmented analytics layer from the ground up.

Job Responsibilities

• Build and maintain operational and strategic KPI dashboards
• Analyze client accounts receivable inventory and accounts payable data and historical performance datasets to identify trends anomalies and performance drivers
• Support standardized data capture and consistent documentation to improve downstream reporting and insights
• Automate recurring reports and improve reporting efficiency
• Build and maintain clients collateral monitoring model
• Support the creation/testing of standardized LLM prompt packs for examiner workflows to drive targeted risk identification and efficiency.
• Collaborate on AI-assisted reconciliation and exception-triage workflows
• Evaluate and prototype agentic automation use cases (e.g. multi-step data extraction from Excel files cross-system validation anomaly surfacing)
• Build QA and feedback loops for AI-generated outputs to ensure explain ability accuracy and compliance with model risk and audit standards
• Collaborate with various platform product and process owners across the ABL ecosystem to creatively integrate data and insights
• Establish data quality validation and governance standards

Required Qualifications Skills and Capabilities

• SQL or SQL-like languages proficiency
• Foundational understanding of data modeling and data pipeline concepts (how data moves from source to reporting layer)
• Comfort working with AI-assisted tools and willingness to learn prompt engineering LLM-based workflows and agentic automation concepts
• Strong interpersonal and relationship development skills; effective business writing skills.
• Proficiency in Microsoft Suite of products such as PowerPoint Excel Visio and Project
• Strong analytical skills with attention to detail and accuracy; intellectual curiosity and problem solving.
• Ability to think critically while working in a fast-paced environment.
• Experience in developing complex business analysis models by being resourceful consulting with others and considering alternatives

Preferred qualifications skills and capabilities

• Commercial lending field exam accounting or auditing experience.
• CPA (Certified Public Accountant) and/or CFE (Certified Fraud Examiner).Technical skills to access complex data sources to solve problems; examples include Alteryx Qlik Sense Python BI Tools (PowerBI Tableau) etc.
• Minimum 13 years of work experience; at least 1 year with MIS or Analytics
• Experience with cloud-based data platforms (Snowflake Databricks Starburst AWS Redshift or similar)
• Hands-on experience building data models schemas and ETL pipelines Familiarity with standardized reporting and operational metrics concepts (status tracking workload/productivity measures) and interest in analytics enablement.
• Bachelors degree in Accounting Finance or Data Analytics strongly preferred; other majors considered based on experience and relevant coursework.