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I am a creative problem solver and data whisperer with over 7 years of experience transforming messy, complex data sets into powerful business decisions. I thrive where statistics meets software engineering, whether it's training machine learning models to power recommendation engines, building data pipelines from scratch, or deploying AI solutions to the cloud at scale. Throughout my career, I have built automated extraction pipelines, engineered reinforcement learning systems for investment optimization, and developed scalable AI models to improve data accuracy and decision-making. I am passionate about mentoring others and leveraging cutting-edge cloud and MLOps technologies to deliver impactful business results.…I am a creative problem solver and data whisperer with over 7 years of experience transforming messy, complex data sets into powerful business decisions. I thrive where statistics meets software engineering, whether it's training machine learning models to power recommendation engines, building data pipelines from scratch, or deploying AI solutions to the cloud at scale. Throughout my career, I have built automated extraction pipelines, engineered reinforcement learning systems for investment optimization, and developed scalable AI models to improve data accuracy and decision-making. I am passionate about mentoring others and leveraging cutting-edge cloud and MLOps technologies to deliver impactful business results.

Sergio D. Munoz

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I am a creative problem solver and data whisperer with over 7 years of experience transforming messy, complex data sets into powerful business decisions. I thrive where statistics meets software engineering, whether it's training machine learning models to power recommendation engines, building data pipelines from scratch, or deploying AI solutions to the cloud at scale. Throughout my career, I have built automated extraction pipelines, engineered reinforcement learning systems for investment optimization, and developed scalable AI models to improve data accuracy and decision-making. I am passionate about mentoring others and leveraging cutting-edge cloud and MLOps technologies to deliver impactful business results.…I am a creative problem solver and data whisperer with over 7 years of experience transforming messy, complex data sets into powerful business decisions. I thrive where statistics meets software engineering, whether it's training machine learning models to power recommendation engines, building data pipelines from scratch, or deploying AI solutions to the cloud at scale. Throughout my career, I have built automated extraction pipelines, engineered reinforcement learning systems for investment optimization, and developed scalable AI models to improve data accuracy and decision-making. I am passionate about mentoring others and leveraging cutting-edge cloud and MLOps technologies to deliver impactful business results.

Available to hire

I am a creative problem solver and data whisperer with over 7 years of experience transforming messy, complex data sets into powerful business decisions. I thrive where statistics meets software engineering, whether it’s training machine learning models to power recommendation engines, building data pipelines from scratch, or deploying AI solutions to the cloud at scale.

Throughout my career, I have built automated extraction pipelines, engineered reinforcement learning systems for investment optimization, and developed scalable AI models to improve data accuracy and decision-making. I am passionate about mentoring others and leveraging cutting-edge cloud and MLOps technologies to deliver impactful business results.

Skills

Experience Level

Expert

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Expert

Work Experience

Senior AI/ML Engineer at Allocations

August 1, 2024 - Present

Built an automated extraction and classification pipeline for investor contracts using AWS Textract, spaCy, and BERT, reducing manual document review time by 40%. Engineered a portfolio balancing system leveraging reinforcement learning and Monte Carlo simulations for real-time investment optimization, achieving a 30% reduction in balancing time. Utilized real-time batch ETL pipelines with AWS Glue, Kinesis, Apache Airflow, and Step Functions for document processing automation. Implemented scalable machine learning models with TensorFlow and PyTorch to enhance financial data extraction accuracy by 35%. Deployed models on AWS SageMaker with real-time classification improving monitoring accuracy to 99%. Collaborated in agile teams consistently delivering sprint commitments, designed and deployed RESTful APIs using FastAPI integrating ML models for real-time stakeholder insights, improving client reporting time by 50%. Mentored junior data scientists and organized internal sessions on MLO

Machine Learning Scientist at Astro Sirens

July 31, 2024 - August 26, 2025

Developed predictive models in Python and R to forecast mobile app performance and user churn, increasing user engagement by 15%. Improved data accuracy in ETL pipelines by 80% using Selenium and Jsoup libraries for data scraping. Applied NLP and Retrieval Augmented Generation (RAG) techniques with Azure Cognitive Services and Hugging Face to extract insights and automate sentiment analysis and customer support. Developed healthcare predictive models using Azure ML and TensorFlow for patient outcomes. Collaborated in Agile environments deploying models with CI/CD using GitHub Actions and Docker. Created interactive dashboards with Power BI delivering actionable insights for e-commerce performance. Deployed ML models in production using Databricks and Snowflake for scalable real-time predictions. Developed a hybrid clustering-classification model combining KMeans and XGBoost to identify capital call investment scams with 99% detection accuracy, reducing manual review workload by 30%. Op

Data Scientist at Meta

May 1, 2020 - August 26, 2025

Contributed to personalized product ranking model development using deep learning (TensorFlow/PyTorch) improving marketplace search relevance and increasing user engagement by 12%. Collaborated with product and engineering teams to build predictive models for fraud detection using XGBoost and anomaly detection techniques. Performed cohort analysis and A/B testing to optimize email campaigns, increasing conversion by 18%. Conducted advanced feature engineering on multimodal data leveraging NLP, CNN visual encoders, and behavioral sequence modeling. Generated unified embedding spaces for listings using multimodal fusion techniques and deployed vector similarity search with FAISS, improving product discovery CTR by 15%. Partnered with marketing and growth teams to build predictive CLTV models. Developed data labeling strategies and human-in-the-loop pipelines to improve training datasets and reduce bias in ML models.

Business Intelligence Intern at IBM

June 1, 2017 - August 26, 2025

Designed Kimball-based data warehouse models in Oracle to improve storage and retrieval of financial data, enhancing query performance by 40%. Revamped the AML system for internal reporting reducing ETL time by 30%, reporting time by 20%, and data warehouse size by 40%. Delivered data visualizations using SQL and OBIEE for stakeholder reporting, contributing to a 25% revenue increase through targeted marketing insights. Developed and maintained complex ETL workflows using Oracle Data Integrator (ODI), automating data integration and reducing manual processing time by 35%.