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Micaelly Cristine

@micaellycristine

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Data Scientist, AI & Data Engineer | LLMs, RAG, Machine Learning | Python, SQL, PySpark, Databricks, Airflow

Brazil

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What I'm looking for

Fully remote Data Scientist, AI Engineer or Data Engineer role where data and AI are core to the product. I want to take ML and LLM solutions from prototype to production: data pipelines, RAG and GenAI apps, predictive models. I value ownership, async communication and continuous learning. Contractor, no visa sponsorship needed, full overlap with US hours.

I turn messy data into reliable pipelines and AI that actually works in production.

Many companies invest in Generative AI, LLMs and Machine Learning, but their projects never leave the demo stage because the data behind them is scattered, unreliable or late. That is exactly the gap I close.

As a Data Scientist, AI Engineer and Data Engineer, I build the full path, from data ingestion, ETL/ELT and data modeling to the predictive model or AI application that delivers results:

• Built and optimized Big Data financial pipelines with SQL, Oracle PL/SQL and Teradata for a bank serving ~8 million members

• Developed batch data pipelines with Python, PySpark, Databricks and Delta Lake, orchestrated in Apache Airflow with data quality checks, monitoring and CI/CD

• Shipped LLM and RAG applications to production, with embeddings, vector databases, semantic search, prompt engineering, validation and human review

• Published a peer-reviewed Machine Learning study: a Random Forest classification model with 91.42% accuracy, using feature engineering and cross-validation

Tech stack: Python, SQL, PySpark, Apache Spark, Databricks, Airflow, dbt, Pandas, Scikit-learn, TensorFlow, LangChain, FastAPI, Docker, PostgreSQL, AWS, Azure and GCP.

Background: MBA in Data Science and Analytics (University of São Paulo), Bachelor's in Economics with a strong statistics foundation, and Microsoft Azure AZ-900 certification.

Open to remote Data Scientist, AI Engineer, Data Engineer and Machine Learning Engineer roles, as a contractor with no visa sponsorship needed. Let's talk: send me a message here.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

Prysmo

Jan 2026 - Present (10 months)

• Shipped LLM workflows to production with RAG, embeddings and semantic search, plus validation, fallback logic and human review
• Built data pipelines with Python, PySpark and SQL on Databricks (Delta Lake)
• Orchestrated Airflow DAGs with retries, data quality tests and monitoring
• Automated web scraping and served data via Flask REST APIs (JWT), Docker and CI/CD

Airflow Azure DevOps BeautifulSoup Data Orchestration Data Pipelines Docker Docker Compose ETL Flask Git HTTP JSON JWT Linux Playwright PyPDF2 Python requests REST APIs SQL SQLite Web Crawling Web Scraping

Python Developer

Risk3

Mar 2025 - Oct 2025 (7 months)

• Built and maintained Python web crawlers and scraping services feeding production data pipelines
• Created ingestion routines with failure handling, logging and data validation
• Investigated and resolved incidents in Docker/Linux environments
• Worked with Git/GitHub code review, automated testing, documentation and Jira

Docker Git GitHub Jira Linux Python

Data Engineer

Tech6 Group

Jun 2024 - Aug 2025 (1 year 2 months)

Finance, Treasury and Investments team of a cooperative bank serving ~8 million members.
• Developed and optimized Big Data pipelines with Oracle PL/SQL, Teradata and advanced SQL
• Built packages, procedures and tables focused on reliability and performance
• Delivered data via Denodo and Power BI dashboards for investment KPIs

Pl SQL Teradata Excel Figma Microsoft Planner Power BI Denodo Git

Innovation and Entrepreneurship Analyst

Softex

Jul 2024 - Dec 2024 (5 months)

CNPq research fellow in the observatory and intelligence team.
• Collected and analyzed ICT, startup and AI market data
• Built Power BI dashboards and data storytelling for business and institutional audiences
• Wrote articles on innovation, including a paper submitted to the 3rd International Congress of Open Innovation Cases

Excel Word Kanbanize Jamboard Power BI

Tutor - Data Scientist

EBAC - British School of Creative Arts and Technology

May 2024 - Aug 2024 (3 months)

• Mentored Data Science students in Python, SQL and Machine Learning (regression, decision trees, ensemble methods, Random Forest, logistic regression)
• Reviewed projects and code with detailed technical feedback on data preparation, model development, evaluation and debugging

Python Pandas SQL Machine Learning GitHub Git TensorFlow Keras NumPy scikit learn Matplotlib Jira

Junior Back End Developer (PJ)

Seno Tecnologia da Informação

Nov 2023 - Apr 2024 (5 months)

• Built RESTful APIs in Python/Flask with CRUD routes and OAuth2 authentication
• Integrated PostgreSQL and MariaDB through SQLAlchemy ORM, running in Docker on Linux
• Contributed to pull requests, code review, documentation, testing and troubleshooting (Git, Bitbucket, Jira)

Python Flask SQLAlchemy PostgreSQL MariaDB Docker Jira Bitbucket Git Linux

PL/SQL Developer Intern

State Secretariat for Planning and Management (Seplag)

Jun 2022 - Jan 2024 (1 year 7 months)

• Developed and maintained Oracle PL/SQL views, procedures, functions and tables for the state personnel administration system (SEAP)
• Processed data from multiple state departments and supported production troubleshooting
• Built Jasper Reports available for extraction on the system portal

Oracle Pl SQL JavaScript Jasper Gitlab Scrum

Intern Analyst/Data Engineer

Frexco

Jun 2022 - May 2023 (11 months)

• Built Python ETL pipelines in AWS Glue ingesting RD Station CRM API data into a PostgreSQL data warehouse
• Monitored jobs with execution logs and AWS CloudWatch
• Created SQL dashboards in Metabase for data-driven decisions
• Documented pipelines and tables in Confluence

PostgreSQL Python Pandas Metabase Power BI AWS Glue Confluence S3 Cloud Computing Scrum Jira

Education

Degrees, certifications, and relevant coursework

University of São Paulo (USP/Esalq)

MBA, Data Science and Analytics

2022 - 2024

Activities and societies: Machine Learning research project with peer-reviewed publication (RBPO, 2024)

Capstone: Random Forest model predicting fiscal compliance of Mato Grosso municipalities (91.42% accuracy), using feature engineering, cross-validation and Bayesian hyperparameter tuning. Published in the peer-reviewed journal RBPO (Revista Brasileira de Planejamento e Orçamento, 2024).