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DATA SCIENCE

Accelerate your business with hyper skilled Data Scientists that deliver results.

Data Science is an expert field, where methodology and collaboration make the difference

Our Data Science team helps you solve any data challenges leveraging:

  • an advanced expertise in machine learning disciplines
  • a proven industrialisation methodology called Machine Learning Operations
  • a strong collaborative mindset.

Technology – Advanced expertise in data science

Data Science is becoming an expert field with fast and frequent disruptions made of numerous subdomains: Exploratory Data Analysis (EDA), Computer Vision, Natural Language Processing (NLP), Forecasting, Optimization. Each technology bringing its own set of data processing methods, algorithms and challenges.

 

Our Data Science department is divided into dedicated and specialized squads fostering market watch, open-source contribution and innovation:

  • Computer Vision: we help you explore visual data (images, videos) to detect objects, people, themes and even automatically generate new assets.
  • NLP: we help you analyze textual data (tweets, emails, invoices, …) to draw new consumer hidden insights, improve your operational efficiency and automate your response to clients.
  • Forecasting: we leverage all your time series (sales, IoT sensors, …) to help you predict future demand, market shares and detect abnormal trends.
  • Exploratory, Ethical and Explainable Data: we help you have a clearer understanding of hidden insights and potential biases contained in multi-dimensional datasets and black box models.
  • Optimization: we help you improve the efficiency of complex production chains and reduce operating costs (inventory control, network & traffic optimization, workforce allocation, …)

Our career track explicitly rewards individuals who master the latest advancement in every domain, ensuring everyone applies state-of-the-art algorithms in their projects.

Our data scientists bring a strong expertise in each Machine Learning’s sub-field: graduated from the best universities, they are continuously trained via the latest university MOOCs and boot camps that are organised at Artefact.

Machine Learning Operations: a proven methodology ensuring product industrialisation and increased value

In most companies, Data Scientists work in silos without interaction with software engineers. Most of the time they develop one-shot analyses in python notebooks that are costly to migrate to production.

This leads to over-engineering details that do not necessarily have value for the business.

 

A SOPHISTICATED DEVELOPMENT PROCESS

At Artefact we believe that Data Scientists have to be product-focused from the beginning of their development process, meaning they have to think about the industrialisation of software first, before fine-tuning any AI layers. This way of thinking and working ensures a seamless transition from POC to final products.

MACHINE LEARNING OPERATIONS METHODOLOGY

Our Data Scientists follow a strict Machine Learning Operations’ methodology (MLOPS) relying on the application of software engineering’s best practices (versioning, testing, continuous integration and delivery). All along the machine learning production chain, they ensure that every effort in data science is invested towards a valuable and sustainable product to maximise the ROI.