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ABOUT ME
ABOUT ME
Craig Albuquerque
Craig Albuquerque
I am a Data Professional with over 6 years of diverse experience in data analytics, digital transformation, and project management. I am passionate about leveraging data to solve real-world problems.
I have provided exceptional support to clients across various industries and possess hands-on experience in AI/ML model development. Specifically, I have developed machine learning models focusing on survival analytics, computer vision, and Natural Language understanding.
In addition to model development, I have delivered strategic solutions for clients by analyzing revenue data to inform decision-making and evaluating website traffic data for marketing analytics. My passion lies in tackling challenging projects, adopting new technologies, and innovating for efficiency gains.
As you peruse my portfolio, I hope you gain a deeper appreciation for my analytical prowess, creativity, and problem-solving acumen. I am excited about the prospect of applying my expertise to future endeavors and making a meaningful impact in the ever-evolving landscape of data science.
CAREER ROADMAP
CAREER ROADMAP
PROJECT
PROJECT
Auto-regressive Analysis, Forecasting Gold Export Prices in USA.
Tools and Techniques:
Python, ARIMA (Autoregressive Integrated Moving Average, SARIMA, ARIMAX, LSTM.
Predicting Customer Churn using Decision Trees and Ensemble ML Models.
Tools and Techniques:
Python, Scikit Learn, Decision trees, and ensembles.
Visualizing the Professional Landscape through Data Analytics
Tools and Techniques:
Postgre SQL, Python, Data Modeling, Data Cleaning
Exploratory analysis and statistical testing on wildfire trends and patterns.
Tools and Techniques:
Python; Pandas, Seaborn, Statsmodels, Statistical tests: Kruskal-Wallis test, Dickey-Fuller test.
Train a Machine learning model yourself for predicting cost of a used Tesla
Tools and Techniques:
Streamlit, decision trees
Webscaped LinkedIn and analyzed open positions for data-driven decisions
Tools and Techniques:
Google Colab, Python, Beautiful Soup, Matplotlib, Seaborn, numpy, Pandas
Information Extraction - NLU
Information Extraction - NLU
Information Extraction, Fine tuned Transformer, and prompt engineering.
Tools and Techniques:
Spacy, BERT, NLP/NLU, Named Entity Recognition, OpenAI Prompt Engineering
This project is WIP.🏗️👷
SKILLS & CERTIFICATIONS
SKILLS & CERTIFICATIONS
🎓 Professional Certifications
🎓 Professional Certifications
These are the tools I have used and implemented in my journey, of developing myself as a data scientist.
SKILLS
SKILLS
These are the tools I have used and implemented in my journey, of developing myself as a data scientist.
Contact
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