
Senior Lead, Data Analysis
- Hortolândia - SP
- Permanente
- Período integral
- Data Analysis and Interpretation: Conduct in-depth data analysis to identify trends, patterns, and insights that inform workforce strategies and business decisions.
- Stakeholder Engagement: Engage with HR, business leaders, and other stakeholders to understand their data needs and provide tailored analytical solutions that answer their critical questions and drive business outcomes.
- Collaboration with Data Teams: Work closely with data engineers and data scientists to ensure data is clean, structured, and ready for analysis. Participate in designing scalable data pipelines and architectures to support analytical workflows.
- Insights and Data delivery: Utilize data visualization tools (e.g., Tableau, Power BI) and design presentations using PowerPoint to deliver compelling visualizations that communicate basic to complex analytical insights to non-technical audiences.
- Advanced Insights: Surface hidden insights using statistical techniques (e.g., ANOVA, Regression) to uncover drivers of performance or why some groups are more engaged than others to drive business performance.
- Data Quality: Ensure data integrity, consistency, and accuracy across your projects. Collaborate with data governance teams to align processes and maintain high data quality standards.
- Identify opportunities: Monitor requests and find opportunities to automate frequent asks, streamline and help enhance efficiency in our processes, products, and cross-collaboration.
- Have a bachelor or master degree in Computer Science, Data Engineering, IT or related areas.
- Fluent English
- Show strong experience in data analysis, visualization, and interpretation.
- Proficiency with data visualization tools such as Tableau or Power BI.
- Strong proficiency with data management and analysis tools, such as SQL, Python or R, Excel
- Experience designing compelling data stories on presentation tools, such as PowerPoint is preferred
- Formal training in quantitative related fields
- Strong analytical and problem-solving skills.
- Proven experience with simple to advanced analysis, such as descriptive statistics, ANOVA, and regression is preferred.
- Excellent communication and collaboration skills.
- Curious and self-starter
- Ability to work in a fast-paced, dynamic environment.