Description
* Work end-to-end across the data lifecycle: extraction, processing, organization, analysis, and generation of insights for the commercial team.
* Work with large, still poorly structured datasets, organizing and consolidating information from diverse sources.
* Support the commercial and trade teams in identifying growth opportunities (e.g., positive positioning, market share, product mix, coverage, etc.).
* Develop highly granular analyses (by customer, region, channel, and category), guiding focus and prioritization for the team.
* Create and enhance managerial dashboards and reports, ensuring clarity and utility for decision-making.
* Automate routines and processes whenever possible, increasing efficiency and scalability of the area.
* Support building a more robust data infrastructure (e.g., dataset organization, evolution toward BI/Data Lake).
* Actively participate in defining KPIs and metrics that truly drive business performance.
* Document and keep updated the area’s workflows and processes.
Requirements:
What we seek:
Essential Soft Skills
* Analytical ability and logical reasoning to handle data at varying levels of structure.
* Process-oriented mindset, with ability to understand existing workflows and design improvements.
* Ability to manage multiple demands, prioritize effectively, and solve problems in a structured manner.
* Strong communication skills to interact across departments, understand requirements, and translate needs into deliverables.
* Autonomy and proactivity to learn new topics, propose solutions for continuous improvement, and self-manage in a fully remote work environment.
* Hands-on profile, willing to engage both in building and analyzing.
* Organizational skills for documentation, process recording, and control updates.
Essential Hard Skills
* Advanced Excel (formulas, pivot tables, data analysis).
* Experience in data analysis and report development.
* Experience with dashboard tools (Power BI, Looker Studio, or similar).
Nice-to-have (not mandatory, but desirable):
* SQL (queries and data manipulation).
* Python applied to data analysis or automation.
* Experience in process automation and AI agents.