- > 3 ans
- > 3 ans
Docebo powers learning experiences for over 2,600 customers around the world with its easy-to-use, AI-powered Suite designed to close the enterprise learning loop. Docebo’s cloud-based solutions have been recognized by industry publications and analysts as the best enterprise learning technology platform.
Docebo has grown exponentially over the past few years, and has successfully achieved 2 IPOs (TSX: DCBO & NASDAQ: DCBO).
Docebo is now a team of 700+ innovators across the globe. They believe learning is for everyone, and that we all have something we can learn from each other. That’s how Docebo has built a diverse and inclusive community that appreciates one another, learns, and grows together.
As a Data Scientist at Docebo you will be responsible to design and implement a variety of robust and efficient data mining and analysis pipelines using best-in-class programming languages, data manipulation frameworks and tools, drawing from multiple heterogeneous and large-scale data sources, either semi-structured or unstructured. From those pipelines, you will build Machine Learning models to draw statistical insights and predictions for a wide spectrum of applications, and will be responsible for the transition of those models to production.
Reports to: Artificial Intelligence Product Owner
Location: Biassono, Italy - Docebo SpA
- Work and collaborate in a multi-functional team composed of: other Data scientists with various specializations, backend Python software engineers, a data engineer, an MLOps, a Cloud engineer, a scrum master, a product owner and a QA specialist.
- Design, implement, and optimize data mining and analysis procedures and pipelines from multiple loosely associated data sources, including live sources.
- Carry out hypothesis formulation and hypothesis testing.
- Build predictive models using a variety of traditional Machine Learning techniques, as well as neural models, leveraging best-in-class Deep Learning techniques and frameworks.
- Stay up to date with the research and the state of the art related to Machine Learning and Deep Learning algorithms, techniques, and frameworks.
- Conceive and implement methods for continuous learning from “always-on” and streaming data sources over the lifecycle of the Machine Learning models released into production.
- Strong statistics, data mining and machine learning foundations
- At least 3 years of experience in data mining, data analysis, and Machine Learning, working on large-scale projects and heterogeneous data sets
- Strong programming skills within the Python ecosystem
- Considerable experience with major Machine Learning and Deep Learning frameworks and tools, such as scikit-learn, Tensorflow, Pytorch, etc.
- Strong analytical skills
- Strong teamwork attitude
- Fluency in English
- Master degree in Computer Science, Math, Statistics or similar. PhD a plus
- Knowledge and experience with Natural Language Processing, and Deep Learning applications for NLP (such as Transformers), is a major plus
- Knowledge of service-oriented computing, specifically the REST paradigm and micro-services
- Attitude to work and deliver within the context of agile development methodologies
- Hands-on experience with commercial cloud platforms, such as Amazon Web Services and Google Cloud, including the Machine Learning and Natural Language Processing capabilities offered as-a-service by those platforms
- Hands-on experience with big data processing platforms, such as the Hadoop ecosystem or equivalent and with streaming platforms , such as Apache Storm and Spark or equivalent, is a plus.
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