Data Analyst responsible for providing insights by analyzing data for decision-making in the financial sector. Collaborating with various departments to enhance analytical maturity and identify opportunities.
Responsibilities
Integrate and organize data from multiple sources, ensuring structure, consistency, and reliability.
Perform exploratory analyses to identify patterns, trends, and business opportunities.
Develop and maintain dashboards and reports to facilitate monitoring of key indicators.
Ensure data quality by correcting inconsistencies and proposing continuous improvements.
Support analytical models by preparing datasets and contributing to validations.
Communicate insights clearly, turning data into actionable recommendations.
Contribute to digital transformation initiatives and the modernization of analytical workflows.
Create standards, templates, and best practices to strengthen the team's analytical maturity.
Work collaboratively with business teams and other ANBIMA areas to ensure the integrity of processed information.
Collaborate on integrating new data sources that can enrich the quality and depth of KPIs.
Design automated monitoring routines, alerts, and controls for critical KPIs to meet specific business needs.
Act pragmatically and delivery-oriented: maintaining focus, prioritization, and clarity of the area's objectives.
Work in a fast-moving environment with multiple simultaneous demands and challenges.
Requirements
Bachelor's degree in Economics, Data Science, Data Engineering, Mathematics, Statistics, or related fields.
Experience in the financial and capital markets, with background in Asset Management and a focus on the investment funds segment.
Practical experience with fund industry processes, products, risks, and routines, including handling market indicators, economic data, and creating storytelling to support analyses and decision-making.
Expertise in Python for data manipulation and analysis, building automations, ETL pipelines, and supporting the development of statistical and analytical models.
Experience with SQL for advanced queries and query performance optimization, as well as for data integration, modeling, and governance.
Experience with Power BI and Tableau in building dashboards, defining strategic KPIs, visualization, and data storytelling. Advanced Excel skills, including macros (VBA), automation of routines, cross-referencing datasets, and complex analyses.
Hands-on experience with large-scale data manipulation, organization, cleaning, processing, and structuring of high-volume datasets.
Knowledge of Dataiku is desirable for working with analytical workflows and automations.
We are looking for a resilient and adaptable professional able to operate in an environment of constant change and multiple simultaneous demands and challenges.
A versatile and flexible professional, capable of working in diverse contexts with dynamic requirements and varying degrees of complexity.
Strong, concise communication skills required to convey ideas clearly in both technical and business contexts.
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