completeddata
Campaign Effectiveness with PyMC
Bayesian model for estimating expected conversions based on campaign spend and duration.
- Optimization by spend and duration
- Optimal scenarios and heatmap
- Expected conversion modeling
Projects
Case studies that explain the problem, the system behind it, and the decisions that made the work hold up.
completeddata
Campaign Effectiveness with PyMC
Bayesian model for estimating expected conversions based on campaign spend and duration.
- Optimization by spend and duration
- Optimal scenarios and heatmap
- Expected conversion modeling
completeddata
Campaign Response with PyMC
Bayesian model for estimating customer response to marketing campaigns and improving budget allocation.
- Prediction of email campaign response
- Foundation for segmentation and personalization
- Budget optimization by channel
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Complete PyMC Documentation
Comprehensive guide in English on PyMC, its distributions, inference, and resources for learning Bayesian modeling.
- Extensive guide on distributions and models
- Official resources and useful references
- Didactic and practical approach
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Critical Skills with PyMC
Bayesian analysis to identify the skills that most influence project success.
- Skill weights by project
- Credible intervals and relative importance
- Top priority projects
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Customer Segmentation with PyMC
Bayesian segmentation to group customers and prioritize sales actions with FastAPI and Flutter.
- Bayesian customer clustering
- Weights, responsibilities, and cluster centers
- Visual app for exploring results
completeddata
Employee Turnover with PyMC
Bayesian model for estimating HR turnover risk using tenure, satisfaction, salary, and workload.
- Turnover prediction with Bayesian logistic regression
- Key signals: tenure, satisfaction, salary, and workload
- Early identification of at-risk employees
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Financial Risk with PyMC
Bayesian estimation of VaR and critical loss probability with FastAPI and Flutter.
- Value at Risk with Bayesian inference
- Configurable critical loss threshold
- Validation and smoke tests
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Financial Risk with PyMC
Bayesian estimation of VaR and critical loss probability with FastAPI and Flutter.
- Value at Risk with Bayesian inference
- Configurable critical loss threshold
- Loss histogram in Base64
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Future Skill Gaps
Bayesian analysis to estimate future skill gaps and anticipate talent needs.
- Skill gap estimation
- Prediction of future needs
- Frontend for visualizing gaps
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Future Skill Gaps with PyMC
Bayesian analysis to estimate future skill gaps and anticipate talent needs.
- Skill gap estimation
- Risk diagnosis and development focus
- Probabilities and convergence metrics
completeddata
High-Value Leads with PyMC
Bayesian model for prioritizing leads by conversion probability and sales response.
- Lead scoring by conversion
- Priority based on interaction and response
- Clear, stable manual API contract
completeddata
High-Value Leads with PyMC
Bayesian model for prioritizing leads by conversion probability and commercial response.
- Lead scoring by conversion probability
- Priority based on interaction and response
- Clear, stable manual API contract
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Inventory and Logistics with PyMC
Bayesian model for demand, inventory, and logistics lead times focused on reducing stockouts and costs.
- Inventory optimization with probabilistic demand
- Applied to routes and delivery times
- Better planning under uncertainty
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Job Satisfaction with PyMC
Bayesian model for estimating job satisfaction and detecting at-risk employees with visual support.
- Job satisfaction prediction
- Thresholds for risk cases
- Flutter frontend for loading and review
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People Analytics with PyMC
Exploration of skill-based organization and probabilistic analysis for talent decisions and capability gaps.
- Probabilistic skill and talent gap modeling
- Application to skill-based organization
- Focus on development and assignment decisions
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Price Optimization with PyMC
Bayesian model for estimating elasticity, demand, and expected revenue to find more profitable prices.
- Price-demand elasticity estimation
- Optimal price calculation by expected revenue
- FastAPI backend and Flutter client
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Product Demand with PyMC
Bayesian model for estimating future demand and supporting product, inventory, and launch decisions.
- Demand prediction with Bayesian inference
- Support for product and inventory planning
- Useful model for uncertain scenarios
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Sales Forecasting with PyMC
Bayesian model for estimating future sales with FastAPI and Flutter, focused on intervals and visualization.
- Bayesian forecast of future sales
- FastAPI API + Flutter app
- Uncertainty intervals and Base64 chart
completedsecurity
Security Risks with PyMC
Bayesian model for estimating breach probability and detecting suspicious events in network patterns.
- Probabilistic detection of malicious events
- Risk analysis with network variables
- Configurable threshold for high risk
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Talent Assignment with PyMC
Bayesian optimization for assigning employees to projects based on skills and requirements.
- Matching between skills and projects
- Compatibility matrix and heatmap
- Suggested assignments for HR
completeddata
Training Impact with PyMC
Bayesian evaluation of the effect of training programs on skills before and after.
- Before/after training comparison
- Employees with significant improvement
- Results visualization and per-record detail
wipbackend
Backend Python + API Gateway
Evolution from monolith to API Gateway architecture in Python to demonstrate system redesign capability when growth demands it.
- Evolution from monolithic to API Gateway architecture
- Design for future growth and scalability
- Capability to redesign existing systems
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Flutter + Go Application
Full-stack application combining mobile frontend in Flutter with Go backend to demonstrate user experience integration with real systems.
- Full-stack Flutter (frontend) + Go (backend) integration
- Functional product connecting user experience with real backend
- Developed and operational in test environment
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Modular Microservices in Go
Scalable backend system built with a microservices architecture in Go to demonstrate the ability to design decoupled systems.
- Modular microservices architecture in Go
- Scalable, decoupled backend system
- Service organization for maintenance and evolution
activefullstackfeatured
WebVinext Platform
The next iteration of my personal site: a content-driven portfolio rebuilt for Cloudflare Workers with a stronger editorial system and cleaner runtime boundaries.
- Rebuilt personal site on Cloudflare Workers for better runtime alignment
- Implemented validated MDX content layer for structured publishing
- Strengthened editorial visual language and platform architecture integration
completedfullstack
Webastro
The previous portfolio generation built with Astro, used as the editorial and structural baseline for the next platform iteration.
- Established durable content model for structured publishing
- Created intentional project narrative around problem/role/outcome
- Set editorial baseline for stronger messaging in Vinext version
activebackendfeatured
Clawdbot
Automation-first assistant for operational workflows, designed to reduce repetitive handling and turn recurring tasks into guided command flows.
- Reduced manual handling for repeatable operational requests
- Improved consistency through explicit command flows
- Increased traceability with explainable guided actions