AI Strategy & Data Science Manager

Deloitte France; Los Angeles (CA); On-site; USD 156,000 - 307,000; Full time

Job summary

Deloitte, via SFL Scientific, seeks a Data Science Manager to lead a team delivering AI solutions across healthcare, life sciences, manufacturing, and more. You will set technical direction for client engagements, mentor staff, and drive state-of-the-art AI across NLP, time-series, CV, and graph models.

You will collaborate with data scientists, engineers, and architects to ensure production-ready deployments and adhere to governance and best practices.

Qualifications

• Master’s or PhD in a relevant STEM field.
• 6+ years in data science, data engineering, software engineering, or MLOps.
• 6+ years in AI/ML algorithm development and data analysis across NLP, time-series, CV, graph models.
• 6+ years in core programming with Python and ML packages; Docker/Kubernetes experience.
• 4+ years of team management and delivery of complex projects.
• Live within commuting distance to Deloitte offices; 10% travel on average.
• Limited immigration sponsorship may be available.

Responsibilities

• Develop and manage a team to deliver AI solutions across industries.
• Define project strategy and lead solution development for clients.
• Provide technical leadership for AI initiatives and model deployment.
• Mentor junior data scientists and grow delivery capabilities.
• Engage clients to communicate findings and options for deployment.

Skills

Data science leadership

Communication

Project management

Mentoring

Client engagement

Education

Master’s or PhD in STEM

Tools

Python

Keras

PyTorch

Pandas

Scikit-learn

Docker

Kubernetes

AWS

Azure

GCP

Job description

Deloitte, via SFL Scientific, seeks a Data Science Manager to lead a team delivering AI solutions across healthcare, life sciences, manufacturing, and more. You will set technical direction for client engagements, mentor staff, and drive state-of-the-art AI across NLP, time-series, CV, and graph models.

You will collaborate with data scientists, engineers, and architects to ensure production-ready deployments and adhere to governance and best practices.