Accelerator Data Scientist (Lyon)

• Work with business teams to understand requirements, and translate them into technical needs
• Apply data science expertise in machine/deep learning, statistics, forecasting and optimization to multiple AI projects/products
• Gather/organize large & complex data assets, and perform relevant analysis to propose and implement relevant data models for each business case
• Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies
• Work on full-spectrum of activities, from conducting ML experiments to delivering production-ready models
• Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products
• Work with developers, engineers, and MLOps to industrialise and deliver scalable AI/ML solutions
• Participate and contribute to the global data science community of practice
• Be accountable and responsible for the robustness of the AI solution
• Apply responsible AI framework and governance best practices such as monitoring, explainability, trustworthy, ethical
• Mentor junior data scientists and analysts providing guidance in career development and technical growth
• 5 to 8 years' experience
• Experience developing deployable code and deploying models in product-focused development under an agile environment
• Experience in production-ready software development
• Track record of applying machine learning/deep learning approaches to solve various problems (commercial, industrial, research)
• Experience with database mining, big data, and large-scale virtual screening
• Experience in a healthcare company is a strong plus
• Experience in Io

T and timeseries forecasting is a plus**Soft skills**:

• Excellent written and verbal communication skills
• Experience working with multiple teams to drive alignment and results
• Service-oriented, flexible, positive team player
• Self-motivated, takes initiative
• Problem solving & critical thinking**Technical skills**:
• Expertise in business analysis, data visualization and data storytelling
• Expertise with core data science languages (such as Python, R), and familiarity with different database systems (e.g. SQL, No

SQL, graph, timeseries)

• Expertise with sensitive data in critical environments (healthcare, defense, etc.)
• Expertise within most of the following areas: supervised learning, unsupervised learning, deep learning, LLMs, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, optimization
• Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark)
• Hands-on AI/ML modeling experience of complex datasets combined with strong understanding of theoretical foundations of AI/ML (CI/CD, Orchestration)
• Experience in data visualisation technologies and librairies of Tableau, Power BI, Streamlit, Plotly, seaborn or similar
• Experience with various enterprise-level Application Programming Interfaces (APIs)
• Good knowledge of AI regulations**Education**:

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