Strategic AI Data Scientist for Client Transformations

Deloitte France; Kansas City (MO); On-site; USD 96,000 - 188,000; Full time

Job summary

Deloitte France, through its SFL Scientific unit, is hiring a Data Scientist to collaborate with clients on AI/ML solutions across diverse domains. You will design and develop novel projects, work with interdisciplinary teams, and contribute to a growing data science practice focused on strategic AI initiatives.

Ideal candidates have advanced degrees, 2+ years in AI/ML, and experience deploying models in cloud environments.

Qualifications

• Master's or Ph.D. in a relevant STEM field and strong data science background.
• 2+ years in AI/ML algorithm development using Python, PyTorch, and data analysis.
• 2+ years deploying ML models with Kubernetes, Docker, and ML frameworks.
• 2+ years with cloud deployment (AWS, Azure, or GCP).
• Willingness to travel ~10% and reside near Deloitte offices.
• Limited immigration sponsorship may be available.

Responsibilities

• Guide clients with AI strategy and development from exploration to production.
• Deliver AI/ML solutions and provide thought leadership.
• Research and implement novel ML methods and optimize hardware.
• Validate AI models via reviews and tests.
• Prioritize project performance and ensure business impact.
• Collaborate with data engineers and clients to align deliverables with objectives.

Skills

Python

PyTorch

NLP

Time-series analysis

Computer vision

Kubernetes

Docker

MLflow

AWS/Azure/GCP

Strong communication

Education

Master's or Ph.D. in a relevant STEM field

Tools

TensorRT/Triton

RAPIDs

Kubeflow

LangChain

Job description

Deloitte France, through its SFL Scientific unit, is hiring a Data Scientist to collaborate with clients on AI/ML solutions across diverse domains. You will design and develop novel projects, work with interdisciplinary teams, and contribute to a growing data science practice focused on strategic AI initiatives.

Ideal candidates have advanced degrees, 2+ years in AI/ML, and experience deploying models in cloud environments.