🌎 Location: Montréal, Québec, Canada
🔗 LinkedIn: https://www.linkedin.com/in/annthomygilles
📖 Fundamentals of Data Engineering (∼50%)
Senior Data Consultant and Data Scientist with extensive experience in Information Management and Data Analytics. Adept at designing and implementing innovative solutions across various industries, including government, automotive, and IT consulting. Proficient in Python, R, Big Data technologies, and Machine Learning. Passionate about leveraging data to drive actionable insights, improve processes, and support decision-making.
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Dashboard Project - Private 📊💻
- Building a dashboard connected to a database using Flask, mySQL, and web scraping.
- Implemented automatic notifications sent to Discord and Telegram.
WhatsApp Integration - Private📱💬
- Building a Python pipeline connected to a database using Flask,
- MongoDB, and Docker. Implemented API integration with WhatsApp for automated messaging.
Weather Data Aggregation with Kafka - Public ☁️🌡️
- Building a project to scrape weather data from different APIs.
- Experimenting with Kafka to aggregate the data.
- Integrating Spark for data analysis and processing.
- Project is focused on learning Kafka and expanding knowledge of big data technologies.
- Worked on a graph-based modelling project for COVID-19 infection spread and management.
- Gained experience with Neo4j, ElasticSearch, PostgreSQL, MongoDB, Prefect, Dask, Python, Apache Airflow, Unit testing, CI/CD, JIRA, Agile, API, Pandas, and scikit-learn.
- Worked on a DataOps project to clean and prepare data from car sensors for R&D use cases.
- Gained experience with AWS services, Dask, Python, multi Unit testing, CI/CD, JIRA, Agile, API, Pandas, and scikit-learn.
- Developed an automated tool for resume classification and summarization using NLP techniques.
- Gained experience with Python, R, Shiny, MongoDB, TFIDF, word2vec, doc2vec, Random Forest, XGboost, and Docker.
- Built a comprehensive web app dashboard for employee management and tracking.
- Gained experience with Google Cloud Platform (GCP), Docker, web development, Firebase, R, JavaScript, MongoDB, Git, HTML, and CSS.
- Worked on a decision support system for improving doctors prescribing behavior during infectious disease.
- Gained experience with Python, R, inferential statistics, machine learning, dimensionality reduction, business intelligence, metagenomics, differential abundance analysis, nanopore technology, and SQL.
- Developed a differential gene expression analysis workflow using Python, shell, and R languages.
- Gained experience with Tuxedo suite, DeSEQ2, MEME suite, GATK, Picards-tools, Stringtie, Go enrichment, variant calling, and differential expression.
- Characterized virulence factors and vaccine targets of a bacterial canine pathogen.
- Gained experience with cell culture techniques, flow cytometry, genetic engineering, northern and western blotting, fluorescent and confocal microscopy, and PCR.
| Category | Skills |
|---|---|
| Programming | 🐍 Python, R, 💻 Shell/Bash/Command line |
| Databases | 🍃 MongoDB, 🗃️ SQL, 🔗 Neo4J |
| Statistics & Machine Learning | 🔬 Inferential Statistics, 📈 Hypothesis testing, 📊 Regression methods, 🔄 Correlation, 📉 Descriptive Statistics, 🚦 Markov model, 🌐 Dimensionality reduction, 🧩 Clustering, 🌳 Decision tree, 🧠 KNN, 🎄 SVM, 🌱 Random forest |
| Tools | 🧰 Git, 📊 Matplotlib, 🔢 Numpy, 🐼 Pandas, 🍃 Pymongo, 🔬 Scipy, 🤖 Scikit-learn, 🌊 Seaborn, 🔗 SQLalchemy |
| Web Development | 🌐 HTML5/CSS3, 💻 Javascript, Typescript, NestJs, Prisma, 🌶️ Flask |
| Environment | 💻 High Performance Computing, 🐧 Linux |
| Data Science | 🛠️ Data Engineering, 🧑💼 Data Governance, 📈📉📊 Big Data, 🤖 Machine Learning, 📊 Data Analytics, 🍃MongoDB, 🐳 Docker, 🗃️ PostgreSQL, ☁️ Amazon Web Services (AWS), 📈 JIRA, 🌐 Web Development, 🧑🔬 NLP |
Master in Bioinformatics and Statistics (2015 - 2018)
- Three-year Research & Professional Master's Degree in Bioinformatics, Statistics and Mathematics.
- Curriculum covers management, processing, and analysis of sequences and massive data.
- Data science: supervised learning (Regression, Decision Tree, Random Forests, Markov Chains, SVM, KNN, Neural Network) and unsupervised learning (KNN, K-means, CAH)
Master's Degree in Bioengineering and Biomedical Engineering (2013 - 2015)
- Interdisciplinary education in biomedical research and engineering program from various backgrounds including bioengineering, cell and molecular biology, oncology, pharmacology, genetics, and microbiology.
Bachelor's Degree (Licence) in Biochemistry and Biology (2010 - 2013)
- Curriculum covers biochemistry, cellular & molecular biology, immunology, physiology, biological statistics, organic chemistry.