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Data Scientist (ML Ops Specialist) _ TG Quality Foundations

Job Description

The ML Ops Specialist implements, maintains and evolves the platform to enable the development and deployment of machine learning models for the Quality Foundation Technology Group (QFTG). He/she works closely and collaboratively with DevOps, developers and data scientists.

The ML Ops Specialist provides solutions that enable :

• Model production (training)
• Set up the software environment (any tools needed to use the models)
• Optimize infrastructure and deployment in production (collaboration with Ops and developers)
• Improve quality (quality assurance)

Responsibilities:

The main and usual duties of this job are:

• Deploy and operationalize ML models
• Contribute to the industrialization of products using Generative AI and/or Machine learning
• Set up software infrastructure
• Implement model validation
• Contribute to the creation of new models, with a focus on their production.
• Contribute to the quality of models and data generated from them (e.g., set up a QA-friendly environment).
• Identify problems and determine quantitative approaches and methods to develop solutions;
• Develop tools to solve problems
• Document and define projects including data collection and processing, state-of-the-art approaches, final algorithm, detailed results and analytical criteria;
• Collaborate with colleagues (Developers, Dev Ops, Research Scientists) and managers internally and externally to share relevant complex information;
• Contribute to the identification of approaches and the development of new or improved technical tools;
• Act as a consultant to guide technologies and/or advise on proof-of-concepts for forecasting/prescription and AI projects;
• Mentor less experienced colleagues;
• Perform all other related tasks.

Qualifications

Education:

• Bachelor's or Master's degree in computer science, computer or software engineering or equivalent.

Relevant experience:

• 3 to 5 years of complex experience and in-depth expertise related to the position.

Skills and knowledge:

• Experience with ML frameworks
• Proven knowledge of ML/AI platforms and workflows.
• Ability to use and develop proven machine learning algorithms and related methods;
• Ability to configure, use and develop data management systems;
• Ability to understand the tools used by data scientists and experience in software development and test automation.
• Software engineering skills;
• Knowledge of distributed computing to ensure model learning;
• Passion for leveraging data science to solve problems;
• Ability to assess problems quickly, both qualitatively and quantitatively;
• Team player with excellent organizational, interpersonal and communication skills;
• Business/company values orientation;