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Sr Client Data Analyst

30+ days ago 2026/06/23
Other Business Support Services
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Job description

Mission

JOB PURPOSE: 



The Senior Client Data Analyst serves as the strategic bridge between Finance, Treasury, and Operations, ensuring the integrity of the revenue cycle through advanced data architecture and predictive analytics. Reporting to the Treasury Manager, this role is essential for mitigating financial risk, optimizing working capital, and driving the digital transformation of client-facing financial processes.



Profile

RESPONSIBILITIES/DUTIES 



Advanced Financial Analytics & Risk Mitigation



•Lead the analysis of client communications, case histories, and dispute patterns to proactively identify systemic risks and root causes of payment delays.



•Monitor and analyze complex aging receivables and cash-in data to ensure ledger accuracy and facilitate early detection of credit risks.



•Evaluate client payment behaviors and historical trends to provide actionable insights that optimize collection strategies and minimize bad debt exposure.



•Audit the e-invoice lifecycle including issuance, acceptance, and rejection phases to streamline the billing workflow and prevent downstream collection bottlenecks.



Strategic Reporting & Digital Transformation



•Architect and automate analytical dashboards (e.g., Power BI, Tableau) that provide real-time visibility into receivables and collection KPIs.



•Design integrated monitoring systems for back-to-back invoicing to track the full financial lifecycle from supplier cash-out to client cash-in.



•Engineer data-driven forecasting models that provide the Treasury department with high-precision inputs for global cash flow planning.



•Innovate reporting frameworks by migrating manual data sets into scalable, automated cloud-based environments to enhance organizational agility.



Cross-Functional Leadership & Operational Excellence



•Reconcile high-volume client data across Finance, Treasury, and Operations, spearheading process improvements where data silos or discrepancies are identified.



•Spearhead data-driven presentations for senior management, banking partners, and key stakeholders to support high-stakes financial negotiations and audits.



•Direct on-site communications and client-facing meetings by providing empirical evidence to resolve complex disputes and strengthen commercial relationships.



•Advise the Treasury Manager on day-to-day liquidity shifts and operational tasks, serving as a technical subject matter expert for the broader finance team.



Safety Responsibilities:



•Promote a positive safety culture within the workplace and attend any safety-related meetings or briefings as required within the job role.



•Comply with the requirements of RDMC RQHSE Policy and Safety Management System.



•Be mindful that Safety, Security, and Environmental protection are everyone’s responsibility. All staff members are accountable for reporting and intervening in any Safety, Security, or Environmental violations.



ESSENTIAL QUALIFICATIONS, KNOWLEDGE & EXPERIENCE



QUALIFICATIONS: 



•Bachelor’s degree in Finance, Data Science, or Business Administration. 



•Professional certification in data visualization (e.g., Microsoft Certified: Power BI Data Analyst Associate) or finance (e.g. CMA) is an advantage.



KNOWLEDGE: 



•Advanced command of Power BI (DAX/Power Query), SQL, and ERP systems (SAP, Oracle, or Microsoft Dynamics 365), is an advantage.



•Deep understanding of Accounts Receivable (AR) lifecycles, GAAP/IFRS standards, and e-invoicing regulatory frameworks.



•Deep knowledge of data privacy laws.



EXPERIENCE: 



•5–7 years of progressive experience in financial data analysis, revenue operations, or treasury analytics.



DESIRED BEHAVIORS & EXPERIENCES



•Proven track record of transforming "raw data" into clean, executive-ready narratives that drive decision-making.



•Ability to challenge the status quo and influence cross-functional stakeholders without direct authority.



•A forward-thinking approach to AI and Machine Learning applications in predictive financial modeling.



•High emotional intelligence when managing complex client disputes or high-pressure month-end closing cycles.



•High level of professionalism, ethical conduct, and integrity.




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