JUNIOR BUSINESS SUPPORT EXECUTIVE

Description

Position Summary: This role seeks a professional to analyze, exploit, and model control-area data, designing automated solutions to optimize operational efficiency and mitigate risks. Key Highlights: 1. Design and optimization of scripts and ETLs to automate data flows. 2. Extraction and analysis of large volumes of transactional data. 3. Leadership in continuous improvement and digital transformation. Execute data analysis, exploitation, and modeling for control-area processes, aiming to design and implement automated solutions and continuous improvements. This is achieved through the use of advanced technological tools, enabling optimization of operational efficiency, strengthening of existing controls, and generation of efficient early-warning alerts for risk mitigation. In this role, you will have the opportunity to: Process and Control Automation: Design, develop, and optimize scripts and ETLs (using technological tools and AI) to automate daily operational control data flows, reducing manual workload and mitigating operational errors. Data Analysis and Reporting: Extract, clean, and analyze large volumes of the brokerage’s transactional data to transform them into management dashboards, facilitating timely monitoring and data-driven decision-making. Leadership in Continuous Improvement: Proactively act as a technological Change Agent within the “Brokerage of the Future” Transformation Project, challenging traditional ways of working through digital innovation. Data Quality Assurance: Validate consistency, integrity, and reconciliation of customer financial instruments and proprietary portfolio data, ensuring regulatory compliance reports are generated using reliable data. To succeed in this position, you need: Education: A university degree in Information and Management Control Engineering, Civil Engineering, Data Science, or a related field with strong analytical orientation. Programming Languages: Proficiency in Python (data manipulation libraries such as Pandas, NumPy, etc.). Databases: Knowledge and experience with SQL (queries, joins, view creation, and query optimization). Proficiency in Microsoft and Google ecosystems. Data Management: Solid expertise in data processing, manipulation, and governance.