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RPA Bussiness Analyst
People Prime World WideMumbai7 days ago
Job descriptionDevelop dashboards and reports to support FP&A and operational decision-making. Track KPIs and performance metrics across partner, client, and service Collaboration : Work closely with Finance, Risk, HR and other teams to understand business needs and translate them into analytical outputs. Partner with senior SMEs to define long-term data model requirements and platform & Model Development : Support the design and documentation of scalable data models and reporting structures. Contribute to the development of requirements for the enterprise data : Bachelors degree in Finance, Data Science, Business Analytics, or related field. 24 years of experience in process or business analysis, preferably in a finance environment. Strong proficiency in Excel, SQL, and data visualization tools (e.g., Power BI, Tableau). Familiarity with ERP systems (SAP S / 4HANA preferred) and financial modeling. Excellent communication and stakeholder management skills. Experience in hyper-automation, RPA, Agentic solutions areas. Ability to work independently and manage time effectively in a part-time Attributes : Experience with data governance and sourcing frameworks. Exposure to collections, billing and other F&A processes. Understanding of data platform architecture and analytics strategy.
Role Summary :
We are seeking a highly analytical and collaborative Data Analyst to support our Intake team.
This role will be instrumental in sourcing, analyzing, and interpreting data to uncover trends and insights that drive operational improvements across partner, client, and service levels.
The analyst will also contribute to the design of a long-term data model and help define requirements for our evolving data platform.
Key Responsibilities Sourcing & Integration :
- Collaborate with the Data Sourcing team to access and validate data from multiple systems.
- Identify and resolve data conflicts and inconsistencies across & Reporting :
- Analyze billing and collections data to identify trends, anomalies, and opportunities for process
improvement.
(ref : hirist.tech)
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