Ronald Marques Pio
Data Scientist & Analytics Engineer focused on turning messy data into decisions — dashboards, automation, and predictive models.
What I deliver
OutcomesBusiness-driven analytics, built to scale
I’ve worked end-to-end with data from multiple sources — flat files, relational databases, and external APIs —
designing workflows that transform raw, inconsistent inputs into reliable, analysis-ready datasets.
My work typically involves data cleaning, normalization, and validation, followed by the creation of
automated pipelines for reporting, monitoring, and decision support.
These solutions have been applied to real business contexts such as performance tracking, operational monitoring,
demand analysis, and management reporting, always with a focus on clarity, consistency, and scalability.
When applicable, I also develop predictive models to support planning and risk assessment, ensuring that results
are interpretable and aligned with business needs.
Interactive projects
Three hands-on apps you can open right now.
For demonstration purposes only
Experience snapshot
Background across data, IT support, training, and business operations.
- Designed and maintained automated data pipelines using Python and SQL.
- Built dashboards and monitoring tools to support operational and management decisions.
- Integrated data from APIs, spreadsheets, and databases into consistent reporting flows.
- Provided technical support and training focused on practical, business-oriented outcomes.
- Developed internal reporting solutions and performance indicators for business teams.
- Automated recurring analyses to reduce manual effort and improve data reliability.
- Collaborated with stakeholders to translate business questions into analytical solutions.
- Worked with structured and semi-structured data from multiple sources.
- Implemented data cleaning, validation, and standardization processes.
- Created analysis-ready datasets to support KPIs, trend analysis, and forecasting.
Technical strengths
Tools and technologies I use to build reliable, business-focused data solutions.
Data & Analytics
- Data cleaning, validation, and standardization
- Exploratory Data Analysis (EDA)
- Statistical analysis and KPI definition
- Feature engineering and data preparation
- Machine Learning (supervised models, evaluation, interpretation)
- Business analytics and performance monitoring
Tools & Stack
- Python (Pandas, NumPy, Scikit-learn)
- SQL (PostgreSQL, SQL Server, MySQL)
- Power BI (dashboards, DAX, data modeling)
- Flask APIs and lightweight data apps
- ETL pipelines and data automation
- Integration with external APIs and files
Communication & Delivery
- Translation of business needs into data solutions
- Clear reporting for technical and non-technical audiences
- Dashboard storytelling and insight communication
- Documentation and knowledge transfer
- Training and mentoring (technical & business users)
- SCRUM fundamentals and collaborative work
Education & certifications
- Postgraduate in Big Data & Data Science
- Graduation in IT Management
- Postgraduate in Business Management
- Graduation in Management Processes