Data Scientist

Contenu de l'offre Data Scientist chez Wolters Kluwer

Enablon, a Wolters Kluwer company, is the leading provider of integrated software solutions for risk management, operational risk management, EHS and sustainability. Hundreds of industry-leading companies and millions of users worldwide rely on our solutions to mitigate risk, improve employee safety, prevent incidents and achieve compliance.

In January 2020, CGE Risk joined forces with Enablon to form a business unit within Wolters Kluwer. From the beginning, Enablon's mission has been to help create a better world by making organisations safer, more efficient and more sustainable through technological innovation.

Today, this mission is more relevant than ever: the possibilities of Industry 4.0 data and platform intelligence make this a fantastic time for our industry. We have an incredible opportunity to change the world we live in and do great things for the organisations and colleagues we serve. The journey from managing risks and incidents to preventing them is extremely rewarding and we look forward to sharing this journey with our clients.

Enablon's approach to helping companies manage EHS, Operations, Risk and Sustainability does not go unnoticed. We are consistently recognised by analysts, industry associations and the media as a global leader and visionary.

We are a fast-growing international company operating in more than 130 countries. Our global headquarters and main R&D departments are located in Paris (Bois-Colombes) and The Hague, with North American headquarters in Chicago and offices in Houston, London, Madrid and Montreal. Through its network of partners, Enablon is active in more than 130 countries. Our solutions make a difference - and so do our people.

Enablon is expanding its R&D development team in France! To support the stronger demand for our data-driven solutions and as part of our strategy to expand in France, we are currently looking for a Data Scientist to be based in France/Paris.

As a Data Scientist at Enablon R&D, you will have an exciting opportunity to explore greenfield projects and contribute to building innovative solutions.

Job Responsibilities :

o Collaborate with other software developers, data / machine learning engineers, product owners and managers to plan, design, prototype and evaluate AI/machine learning driven applications.

o Provide machine driven recommendations to augment human expertise and intelligence in mitigating industrial risk.

o Contribute to the development of advanced predictive models and machine learning models using current technology and other available tools.

o Perform a range of technical assignments and solves moderately complex problems under guidance of established policies and procedure.

o Research and review relevant academic literature and AI/data science techniques leveraging industry 4.0 derived data assets.

o Contribute to delivery of team goals through personal efforts or through influence over team members.

o Review pull request of the team and give recommendation to improve code quality and best practice.

o PoCs, APIs, MVPs developed on-time and on-budget.

o Integration with external third party systems or services.

Profile :

Masters of Computer Science, AI / Machine Learning / Applied Mathematics. Skills in programming : Python, R. Competencies in AI/Machine learning: scikit learning / pandas, NLP, deep learning frameworks, computer vision. Good grasp of statistical tests and design of experiment and sampling techniques. Hands-on experience and knowledge of the standard tools for continuous integrations and dashboards in the software industry, and can program / automate with proficiency using scripting languages. Technologies include docker, Azure ecosystem, Terraform, bash, etc. Familiarity with database technologies such as PostgresSQL, Oracle, and MongoDB. Ability to work independently while maintaining focus on achieving optimal outcomes as part of a collaborative development effort. A can-do person with a constructive mindset, a team player. Work within Agile processes.