Lead Data Scientist
2022 - PRESENTKoble- Developed an NLP service that describes any company activity and products given their raw website.
- Created an NLP service that classifies companies according to a taxonomy of sectors.
- Devised a classification/prediction pipeline that predicts startup success probability given market, team, and funding features.
- Introduced good data science practices and processes to the team.
Technologies: Amazon S3 (AWS S3), APIs, REST, Kubernetes, AWS Lambda, Amazon SageMaker, Elasticsearch, BERT, Large Language Models (LLM), Sentiment Analysis, Text Classification, Data AnalysisMachine Learning Consultant
2022 - 2022Telescope- Developed an automated email writing service based on historical emails and generative AI.
- Created a recommender system that suggests people contact based on previous people searched, keywords, and company description.
- Built an email classification system that classifies emails based on type. e.g., sales, inquiry, follow-up, and more.
Technologies: Amazon Web Services (AWS), Amazon S3 (AWS S3), AWS Lambda, Elasticsearch, Recommendation Systems, BERT, Sentiment Analysis, Computational Linguistics, Large Language Models (LLM), Text Classification, Data AnalysisMachine Learning Consultant
2020 - 2022Springbok- Developed a system using GPT-3 to automatically create questions and answers from documents, feeding them to a chatbot system answering customers' queries.
- Created a microservice for the linguistically aware natural language understanding (NLU) model to recommend text style correction for technical requirements.
- Produced machine learning (ML) services for multiple natural language processing (NLP) tasks, including text classification and recommendation.
Technologies: Python 3, Rasa NLU, Generative Pre-trained Transformer 3 (GPT-3), PyTorch, TensorFlow, APIs, Microservices, Recommendation Systems, Natural Language Understanding (NLU), NLU, PostgreSQL, Amazon S3 (AWS S3), Artificial Intelligence (AI), Docker, Kubernetes, Machine Learning, Data Science, Jupyter, REST APIs, Annotations, Amazon Web Services (AWS), Flask, Chatbots, Linux, MacOS, PyCharm, Mathematics, Statistics, Programming, Computational Linguistics, Natural Language Processing (NLP), Machine Learning Operations (MLOps), Continuous Delivery (CD), Continuous Integration (CI), Software Engineering, NumPy, Data Reporting, SciPy, Jupyter Notebook, Matplotlib, NLTK, Convolutional Neural Networks, Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Git, Topic Modeling, Python, SQL, NoSQL, Deep Learning, Neural Networks, Code Review, Task Analysis, Large Language Models (LLM), Sentiment Analysis, Text Classification, Data AnalysisSenior Machine Learning Engineer
2016 - 2020ComplyAdvantage- Built the ML pipeline models to read articles, an information extraction system that feeds into a knowledge graph of criminal and adverse media entities.
- Improved the company's entity extraction and classification system eight times, increasing unique entities in the knowledge graph through implementing the latest NLU research.
- Enhanced the ease of ML model deployment and development by redesigning the monolithic ML pipeline into a microservices-based scalable one.
- Guided the team's growth by helping with research and development projects and managed a junior ML engineer.
- Drove the inclusion of the latest NLP research in the company's solutions.
- Built the ML pipelines and led data collection automation through MLOps practices.
- Introduced an additional entity meta-data for the company's extraction system by developing a relation extractor using distant supervision methods.
- Led a significant refactoring project following a microservices approach to split the company's main article-reading ML pipeline into multiple projects, using Elasticsearch, Kubernetes, Docker, AWS, and CI/CD.
Technologies: Python 3, Amazon Web Services (AWS), Kubernetes, Docker, Helm, CI/CD Pipelines, Natural Language Understanding (NLU), Natural Language Processing (NLP), Machine Learning, Machine Learning Operations (MLOps), ETL, TensorFlow, Keras, PyTorch, Pandas, NLU, Amazon SageMaker, MTurk API, Annotations, Amazon S3 (AWS S3), Continuous Delivery (CD), Continuous Integration (CI), Big Data, Software Engineering, Flask, APIs, Artificial Intelligence (AI), Data Science, NumPy, Data Reporting, Scikit-learn, SciPy, Jupyter Notebook, Matplotlib, NLTK, Convolutional Neural Networks, Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Git, SQL, Topic Modeling, Linux, MacOS, PyCharm, Mathematics, Statistics, Programming, Social Network Analysis, Computational Linguistics, Rasa NLU, Microservices, PostgreSQL, Jupyter, REST APIs, Python, NoSQL, Deep Learning, Data Analytics, Neural Networks, Technical Hiring, Source Code Review, Code Review, Task Analysis, Interviewing, Team Management, Sentiment Analysis, Text Classification, Data Analysis
Fuad Issa
Machine Learning Developer in London, United Kingdom
Member since July 22, 2022
Fuad is an experienced machine learning engineer and data scientist with a background in building major, scalable production systems for information extraction and knowledge base population. He enjoys designing and creating a state of art solutions for custom NLP problems. Fuad is proficient in recent advances and models to build semantic search systems, information extraction, and recommender systems utilizing NLU technologies.
Fuad is now available for hire
Experience
- Natural Language Understanding (NLU) 6 years
- Python 3 6 years
- Computational Linguistics 6 years
- TensorFlow 6 years
- Machine Learning 6 years
- PyTorch 4 years
- Social Network Analysis 1 year
- Recommendation Systems 1 year
Availability
Part-time
Preferred Environment
PyCharm, Python 3, Docker, Kubernetes, Amazon Web Services (AWS), Jupyter Notebook, Git, GitLab, GitLab CI/CD
The most amazing...
...thing I've developed is an information extraction pipeline processing millions of articles to populate a knowledge graph.
Employment
Experience
- Abstract Meaning Representation for Paraphrase Detectionhttps://aclanthology.org/N18-1041/
Master's thesis results published in NAACL 2018. The thesis established that the graph representation of a sentence obtained using Abstract Meaning Representation (AMR) parsers is useful for detecting paraphrases. Achieved state-of-the-art results at the time using a novel PageRank enhanced reweighing method.
- Article Reading System
This project was about an ML pipeline extracting names of people, companies, and sentence relations from millions of article texts to classify them according to a custom taxonomy.
The tasks involved building the models, dataset creation and collection, and data engineering to create the pipeline.
Skills
Languages
Python 3, Python, SQLFrameworks
FlaskLibraries/APIs
PyTorch, TensorFlow, Keras, Pandas, NetworkX, Scikit-learn, NumPy, SciPy, Matplotlib, NLTK, REST APIs, Rasa NLU, MTurk APITools
Git, Jupyter, PyCharm, Amazon SageMaker, Helm, GitLab, GitLab CI/CDParadigms
Continuous Delivery (CD), Continuous Integration (CI), Data Science, Microservices, REST, ETLPlatforms
Jupyter Notebook, Linux, MacOS, Amazon Web Services (AWS), Docker, Kubernetes, AWS LambdaOther
Research, Programming, Natural Language Understanding (NLU), Machine Learning, Computational Linguistics, Natural Language Processing (NLP), Generative Pre-trained Transformer 3 (GPT-3), Recommendation Systems, NLU, Annotations, AMR, Software Engineering, Artificial Intelligence (AI), Data Reporting, Convolutional Neural Networks, Long Short-term Memory (LSTM), Applied Research, Supervised Machine Learning, Topic Modeling, Chatbots, Deep Learning, Data Analytics, Neural Networks, Technical Hiring, Source Code Review, Code Review, Task Analysis, BERT, Sentiment Analysis, Large Language Models (LLM), Text Classification, Google Colaboratory (Colab), Data Analysis, Mathematics, Statistics, Physics, Machine Vision, Social Network Analysis, Bayesian Inference & Modeling, Machine Learning Operations (MLOps), APIs, Big Data, Interviewing, Team Management, Computational Physics, Reinforcement Learning, Graph Theory, CI/CD PipelinesStorage
Elasticsearch, PostgreSQL, Amazon S3 (AWS S3), NoSQL
Education
- Master's Degree in Artificial Intelligence2015 - 2016The University of Edinburgh - Edinburgh, UK
- Master's Degree in Physics and Nanotechnology2014 - 2015The University of Cambridge - Cambridge, UK
- Bachelor's Degree in Physics and Nanotechnology2009 - 2012The University of Leeds - Leeds, UK
