The Junior Data Analyst supports the Finance department's data-driven operations within a 3PL business environment. This role is responsible for verifying logistics carrier invoices, processing and comparing carrier quotation data, and conducting gross margin analysis to support business decision-making and cost optimization initiatives. The role is expected to work AI-first, applying AI and LLM-based tools as the default approach to daily analysis, reconciliation and reporting work.
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Billing Verification & Reconciliation: Review logistics carrier invoices for data accuracy and reasonableness; identify discrepancies and follow up with carriers and internal teams for timely resolution. Maintain records to support audit trails.
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Carrier Rate Data Processing: Collect, organize, clean, and structure carrier rate quotes to enable systematic rate comparison; provide data-backed insights to support pricing negotiations and carrier selection.
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Gross Margin Analysis: Assist in preparing periodic gross margin reports; identify low-margin accounts or shipments, analyze root causes, and collaborate with business teams to surface cost reduction and efficiency improvement opportunities.
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Ad-hoc Data Support: Respond to data requests from internal business units as assigned, including supporting customer pricing tables and fulfilling cross-departmental analytical needs.
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AI-First Ways of Working: Use AI and LLM-based tools as the default approach to daily work — accelerating invoice review, rate data cleaning, gross margin analysis and report drafting. Write and refine prompts, build reusable prompt templates and lightweight AI-assisted workflows for recurring finance tasks, and always validate AI output against source data before it is used in any deliverable. Share effective methods with the wider Finance team.
Requirements
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Bachelor's degree or above in Finance, Accounting, Statistics, Supply Chain Management, or a related field.
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2–3 years of relevant working experience; background in logistics, 3PL operations, or finance preferred.
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Proficient in English for both written documentation and verbal business communication.
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Advanced Excel proficiency including VLOOKUP / XLOOKUP, SUMIF(S), INDEX-MATCH, Pivot Tables, and data validation; ability to build structured, audit-ready workbooks.
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Demonstrated hands-on use of AI tools (e.g. ChatGPT, Claude, Copilot) in analytical, finance or operational work; able to write effective prompts, recognise when AI output is unreliable, and verify results against source data. Candidates should be prepared to describe how they currently use AI in their day-to-day work.
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Strong attention to detail and a rigorous approach to data accuracy; able to detect anomalies in large datasets.
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Comfortable working in a fast-paced, cross-functional environment with frequent changes; proactive and self-driven.
