Enterprise RAG Assistant
Developed enterprise-grade retrieval assistants using GPT-4, LangChain, Vertex AI, embeddings, and document pipelines to support high-accuracy Q&A and knowledge search across business documents.
Data Scientist focused on business impact.
My background combines data engineering depth with applied machine learning and GenAI delivery. I can move from raw data and messy requirements to analysis, modeling, APIs, dashboards, and production-ready workflows.
7+
Years across AI/ML, data engineering, analytics, and cloud platforms
86%
Manual task automation through ChatGPT API integration
30%
Hallucination reduction through prompt iteration and response analysis
25%
User retention lift from context-aware recommendation systems
Core Data Science Skills
A recruiter-friendly skill map for Data Scientist, AI Scientist, ML Engineer, and Applied AI roles.
Machine Learning
- Model development with scikit-learn, TensorFlow, PyTorch
- Forecasting, anomaly detection, risk modeling, recommendations
- Feature engineering, data profiling, EDA, model evaluation
- NLP: sentiment, tokenization, lemmatization, POS tagging, NER
GenAI & LLMs
- RAG assistants with GPT-4, LangChain, OpenAI APIs, Vertex AI
- Prompt engineering, response evaluation, hallucination reduction
- Hugging Face Transformers, BERT embeddings, document intelligence
- LLMOps and guardrails: PromptLayer, Guardrails.ai, TruLens
Data Engineering
- Python, SQL, PySpark, Scala, Spark SQL, Spark Streaming
- Databricks, Delta Lake, Snowflake, Redshift, BigQuery, Synapse
- ETL/ELT with Airflow, Azure Data Factory, AWS Glue, SSIS
- Streaming ingestion with Kafka, Event Hubs, Kinesis, Pub/Sub
MLOps & Analytics
- Vertex AI Pipelines, Kubeflow, Docker, FastAPI, CI/CD
- Model deployment, monitoring, version control, automated testing
- Data validation, lineage, quality checks, masking, encryption
- Tableau and Power BI dashboards for stakeholder decisions
Featured AI/ML Work
Selected examples rewritten from the resume as portfolio-style case studies for a Data Scientist position.
Supply Chain Decision Models
Integrated Generative AI and reusable ML models to support demand forecasting, operational risk mitigation, and supply chain insight generation through automated data workflows.
ChatGPT API Support Automation
Integrated ChatGPT APIs into client-facing workflows, reducing manual support work through contextual interactions and dynamic, production-ready chatbot responses.
Real-Time Analytics Pipeline
Built Spark Structured Streaming and Kafka pipelines with validation checks, anomaly handling, data profiling, and warehouse-ready models for high-volume analytics.
Experience
Positioned for Data Scientist roles while keeping the strongest ML, analytics, and cloud delivery details visible.
Broadway Bank
March 2025 - Present | San Antonio, TX
Build end-to-end ML and GenAI pipelines for forecasting, document intelligence, RAG assistants, and production APIs. Use Python, FastAPI, GPT-4, LangChain, Vertex AI, Snowflake, Azure Data Factory, Databricks, PySpark, Kafka, Docker, Kubernetes, and CI/CD to deliver scalable data science workflows.
Ameriprise Financial
January 2023 - February 2025 | Minneapolis, MN
Delivered NLP, LLM, recommendation, migration, and analytics solutions using Python, Spark, Azure OpenAI, LangChain, Vertex AI Pipelines, Kubeflow, Airflow, Kafka, Snowflake, Redshift, Tableau, and Power BI. Improved prompt quality, reduced hallucinations, automated manual work, and operationalized data quality checks.
Gentiva Healthcare Services
February 2019 - December 2022 | Tampa, FL
Created modern cloud data solutions for analytics and visualization. Built Python, SQL, PySpark, Azure Data Factory, Databricks, Synapse, Data Lake, TensorFlow, and Tableau-connected workflows for data cleansing, transformation, migration, EDA, and client usage trend analysis.
Education
Academic foundation with healthcare, science, technology, and user-centered design context.
Academy of Art University
In Progress
Useful for communicating analytics, designing dashboards, and making AI systems more usable for business stakeholders.
Coleman University
San Diego, CA
Business and operations foundation for translating model outputs into measurable decisions.
Lorma Colleges
Philippines
Scientific foundation in data quality, analysis, validation, and evidence-based decision-making.
Certifications
Additional credentials that support technical leadership, cloud awareness, and secure AI delivery.
Project Management Professional (PMP)
Delivery, stakeholder alignment, scope, and execution discipline.
CompTIA Security+
Security-minded development for data, ML, and cloud environments.
Microsoft Azure Fundamentals (AZ-900)
Cloud foundation for data platforms and AI services.
ServiceNow Certified System Administrator
Workflow, service operations, and enterprise platform knowledge.
Let's connect.
Open to Data Scientist, Applied AI, ML Engineer, GenAI Engineer, and Data Science Analytics roles.
Recruiter snapshot
Data Scientist with hands-on GenAI, NLP, RAG, MLOps, Python, PySpark, SQL, Databricks, Snowflake, Azure, AWS, and GCP experience. Comfortable working with stakeholders, translating model performance into business outcomes, and delivering analytics that are explainable and production-ready.