I am looking for a full-time, remote Data Analyst role where I can apply my expertise in Python, SQL, Power BI, and Advanced Excel. With a strong background in industrial engineering, data collection, and manufacturing costing, I aim to bridge operational experience with data analytics to deliver actionable insights and optimize business processes.

John Lito
@joao_silva
Data Analyst bridging industrial engineering and data science. With a proven track record in operational efficiency and process optimization.
What I'm looking for
Professional Summary & Career Background
Data Analyst with a strong academic and practical foundation in Food and Industrial Engineering, bridging traditional manufacturing domain expertise with modern data analytics. Over the past few years, my work has heavily focused on industrial data collection, productivity analysis, and manufacturing costing. I am now fully committed to a professional transition into data analytics, specializing in transforming complex operational data into actionable business insights. My technical stack includes Python, SQL, Power BI and Advanced Excel, enabling me to build end-to-end data pipelines, predictive models, and executive dashboards.
Key Achievements & Projects
Industrial Absence Management App (Python/Streamlit): Engineered and deployed an interactive executive dashboard for monitoring direct labor indicators, featuring dynamic timeline filters, Pareto analysis, and advanced time-delta calculations.
Building Management & Energy Efficiency Dashboard (Power BI): Developed a multilevel analytical dashboard monitoring 500 buildings across Portugal, integrating Azure Maps geolocalization, custom DAX measures for ESG metrics, and lifecycle renovation risk analysis.
VFFS Film Waste Reduction Model (Advanced Excel): Created a flat relational model and automated operational control dashboard using Power Query and Power Pivot to monitor equipment degradation cycles and reduce plastic film waste in packaging lines.
Machine Learning Attrition Prediction (Scikit-Learn): Built and evaluated classification models (Logistic Regression, Decision Tree, Random Forest) to tackle employee churn, prioritizing Recall and business cost-effectiveness.
Interests & Personal Approach
I approach technical challenges with an analytical engineering mindset, focusing heavily on meticulous data profiling, strict data cleansing, and selecting evaluation metrics that reflect real-world business outcomes. Outside of data analytics, I am an avid practitioner of electric guitar, focusing on rhythm techniques and complex structural problem-solving—a hobby that mirrors my structured, execution-oriented approach to coding and data architecture.
Now I'm looking for, Remote or flexible data analyst roles with international companies, particularly where an established background in industrial operations, manufacturing, or supply chain provides strong functional industry alignment.
Experience
Work history, roles, and key accomplishments
Industrial Operations & Data Analyst
Frijobel
Feb 2011 - Present (15 years 9 months)
Manage daily operational data collection, productivity tracking, and manufacturing costing. Analyze direct labor (MOD) and material usage to reduce waste and eliminate bottlenecks. Build Excel and Power BI reports to provide executive management with actionable shop-floor insights, bridging 15 years of industrial engineering expertise with modern data analytics.
Education
Degrees, certifications, and relevant coursework
Tokyo School
Data Analytics Bootcamp, Data Analytics & Data Science
2025 - 2026
Activities and societies: Hands-on Data Projects, Exploratory Data Analysis, Database Querying
Intensive Data Analytics program covering SQL querying, Python (Pandas, NumPy), Power BI dashboard design, and statistical data analysis. Developed end-to-end data extraction pipelines, exploratory analytics, and interactive visualization models for business decision-making.
Escola Superior Agrária de Coimbra
Bachelor's Degree in Food Engineering, Food Engineering
2000 - 2004
Grade: 12
Activities and societies: Industrial Quality Control, Statistical Process Control, Food Engineering Labs
Focus on industrial process optimization, thermodynamics, statistical quality control, and data-driven problem solving. Applied engineering methodology, quantitative logic, and analytical frameworks to complex operational systems.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Salary expectations
Social media
Job categories
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