Dimitri Sifoua
Chief Data Engineer
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolDimitri Sifoua is a Chief Data Engineer based in Montreal with 8 years of hands-on experience building cloud-native, data-intensive systems and ML pipelines. He blends software engineering and machine learning expertise—spanning Python, Java, Spark, Kafka, TensorFlow/PyTorch and MLOps tools like Kubeflow, MLFlow and DVC—to move models from research into production at enterprise scale. At the National Bank of Canada he progressed from Senior Data Engineer to Chief Data Engineer, leading architecture and platform work that integrates streaming, batch, and orchestration technologies. His background includes end-to-end product delivery as a full-stack ML developer on GCP and practical research experience applying deep learning and NLP to finance and forecasting problems. Colleagues describe him as an engineer who combines pragmatic production instincts (CI/CD, Terraform, Kubernetes) with a researcher’s curiosity for novel models and data-driven experiments.
8 years of coding experience
5 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Université du Québec à ChicoutimiMaster of Engineering - MEng Software Engineering, Master of Engineering - MEng Software Engineering at Ecole d'Ingénieurs du Littoral - Côte d'OpaleCertificate of Proficiency English for Professional Communication, Certificate of Proficiency English for Professional Communication at McGill University
French, English
Stackoverflow
489reputation
41kreached
29answers
8questions
Github Skills (69)
convolutional-neural-networks10
beam-search10
gru10
dimension-reduction10
arxiv10
torchtext10
generative-adversarial-network10
logistic-regression10
linear-regression9
prediction-model9
computational-finance9
random-forest9
technical-indicators9
prediction9
sequence-to-sequence9
Programming languages (8)
Github contributions (5)
dksifoua/Stock-Market-Prediction
Jul 2020 - Sep 2020
Stock Market Prediction on High-Frequency Data Using soft computing based AI models
Contributions:24 commits, 4 PRs, 24 pushes in 2 months
high-frequency-datasoft-computingpythonfrequency-datahigh-frequency
dksifoua/Question-Answering
Mar 2020 - Nov 2022
State of the art of Neural Question Answering using PyTorch.
Contributions:120 commits, 32 PRs, 118 pushes in 2 years 8 months
jenkinspytorchquestionartdeep-learning
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