👋 Hello, I'm Camilo Andrés Cáceres Flórez

🎯 Data Science Expert / Staff Engineer @ Mercado Libre

Ph.D. + EMBA | ML Researcher | Knowledge Sharer

Building data science solutions and ML systems at scale

I'm a Data Science Expert / Staff Engineer at Mercado Libre (NASDAQ: MELI), one of Latin America's largest tech companies. With a Ph.D. in Mechatronics and an EMBA in Strategic Leadership, I bridge ML research with business strategy, working with data science, machine learning, and data engineering teams to deliver impactful solutions.

I'm passionate about sharing knowledge with the ML community through blogging, speaking, and mentorship.

class CamiloCaceres:
    def __init__(self):
        self.role = "Data Science Expert / Staff Engineer"
        self.company = "Mercado Libre (NASDAQ: MELI)"
        self.location = "Bogotá, Colombia"
        self.focus = "ML Systems & Data Science"

        self.education = {
            "phd": "Mechanical Engineering (Mechatronics) @ UNICAMP",
            "emba": "Strategic Leadership @ Valar Institute",
            "meng": "Mechanical Engineering @ UNICAMP",
            "bsc": "Mechatronics Engineering @ UMNG"
        }

        self.expertise = [
            "Data Science & Analytics",
            "Machine Learning & Deep Learning",
            "MLOps & ML Systems",
            "Statistical Modeling",
            "Research & Experimentation"
        ]

        self.currently_working_on = [
            "ML Systems @ Mercado Libre",
            "Collaborating with DS/MLE/DE teams",
            "Learning Causal Inference techniques",
            "Data-driven decision making"
        ]

        self.passionate_about = [
            "Sharing knowledge through blogging and talks",
            "Contributing to the ML community",
            "Mentoring the next generation of data scientists",
            "Bridging research and industry"
        ]

    def say_hi(self):
        print("Thanks for visiting! Let's learn and build together.")

me = CamiloCaceres()
me.say_hi()

• 📊 Data Science & ML: Building ML systems and analytics solutions at scale
• 🤝 Cross-functional Collaboration: Working with data science, ML engineering, and data engineering teams
• 📈 ML Systems: Developing and optimizing machine learning solutions for business impact
• 🔬 Research & Learning: Exploring causal inference techniques and advanced statistical methods
• 🎓 Knowledge Sharing: Mentoring team members and contributing to technical discussions

impact_metrics = {
    "company": "Mercado Libre (NASDAQ: MELI)",
    "role": "Data Science Expert / Staff Engineer",
    "focus": "ML Systems & Data Science",
    "scale": "Latin America's largest tech company",
    "collaboration": "DS, MLE, and DE teams"
}

• 📊 ML Systems - Building and optimizing machine learning solutions at scale
• 📈 Data-Driven Solutions - Delivering analytics and insights for business impact
• 🤝 Cross-Functional Collaboration - Working with data science, ML engineering, and data engineering teams
• 🎓 Knowledge Sharing - Mentoring team members and contributing to technical excellence
• 🔬 Continuous Learning - Exploring advanced techniques in causal inference and statistical methods

• 🎓 200+ citations on Google Scholar across diverse research areas
• 📝 10+ peer-reviewed publications spanning multiple domains
• 🎤 Conference presentations at international venues in ML, robotics, and control systems
• 🏆 Ph.D. in Mechanical Engineering (Mechatronics) from UNICAMP, Brazil
• 🎯 EMBA in Strategic Leadership from Valar Institute
• 🤖 Research areas: Control systems, Robotics, Computer vision, AI-based control, Bio-inspired systems

Visit camilo-cf.github.io for:

• 📝 Technical blog on data science, ML, and ads systems
• 📊 Case studies and insights from real-world implementations
• 🎯 Deep dives into ML techniques and data analytics
• 📧 Newsletter with data science insights and learnings

• Operating GenAI safety and policy reviews
• Evaluation blueprints for GenAI systems
• Blueprint de evaluación para sistemas de GenAI
• Blueprint de avaliação para sistemas de GenAI
• Backtesting ML pipelines before rollout

• 🎙️ Speaker at AI/ML conferences and industry events
• 👥 Technical content on YouTube
• 🎓 Mentor and advisor for ML engineers and teams
• 📖 Sharing lessons from building ML systems at scale

• 📚 10+ peer-reviewed publications spanning diverse research areas
• 🎤 Conference presentations at international AI/ML, robotics, and mechatronics venues
• 🔬 Research domains: Control systems, Robotics, Computer vision, AI-based control, Bio-inspired systems, Agricultural technology, Human-machine interfaces
• 📊 View full publication list on Google Scholar

1. 🎉 Merged PR #4 in camilo-cf/camilo-cf

🔥 Contribution Streak

📈 Comprehensive GitHub Metrics

_{Updated automatically every 6 hours}

📊 Activity Graph (Alternative View)

🐍 Contribution Snake

• 🎓 Ph.D. in Mechanical Engineering (Mechatronics) - University of Campinas (UNICAMP), Brazil, 2020
• 📊 M.Eng. in Mechanical Engineering - University of Campinas (UNICAMP), Brazil, 2016
• ⚙️ B.S. in Mechatronics Engineering - Military University Nueva Granada (UMNG), Colombia, 2014

• 💼 EMBA in Strategic Leadership - Valar Institute

• 📚 10+ peer-reviewed publications spanning diverse research areas
• 🎯 200+ citations across control systems, robotics, computer vision, and AI applications
• 🔬 Research contributions in mechatronics, intelligent systems, and bio-inspired technologies

"Great data science is at the intersection of rigorous methodology, practical impact, and clear communication. The best solutions emerge when we ask the right questions, choose appropriate techniques, and translate insights into action."

Bridging worlds: I combine academic research rigor (Ph.D.) with strategic business thinking (EMBA) to build data-driven solutions that create measurable value. My approach is grounded in three principles:

• 🎯 Impact over complexity - Simple, well-executed solutions often outperform complex ones
• 🔬 Experimentation mindset - Test assumptions, measure results, iterate continuously
• 🤝 Knowledge multiplier - Sharing what I learn amplifies impact beyond individual contributions

Core beliefs:

• Data tells stories, but context gives them meaning
• The best technical solution is one that people actually use
• Continuous learning is not optional—it's essential for staying relevant
• Collaboration and diverse perspectives lead to better outcomes

"Individual brilliance starts projects; collaborative excellence finishes them. The best data science happens when diverse perspectives challenge our assumptions."

Building together: Technical expertise is amplified through effective collaboration. I believe the strongest solutions emerge from:

• 🎯 Diverse teams - Different backgrounds bring unique insights that lead to more robust solutions
• 💬 Open communication - Transparent discussions about challenges, trade-offs, and constraints
• 🔄 Knowledge sharing - What I learn becomes more valuable when I share it with others
• 🌱 Collective growth - Teams that learn together build better products together