Data Scientist
Job Description
About the Company
Publicis Re:Sources is the backbone of Publicis Groupe, the world's most valuable agency group. We are the only full-service, end-to-end shared service organization in the industry, enabling Groupe agencies to do what they do best: innovate and transform for their clients.
Formed in 1998 as a small team to service a few Publicis Groupe firms, Publicis Re:Sources has grown to 5,000+ employees in over 66 countries. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management.
We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. Learn more about Publicis Re:Sources and the Publicis Groupe agencies we support at http://www.publicisresources.com/.
About the Role
We are seeking a highly skilled Junior Data Scientist to join our team. The ideal candidate will have a strong background in both machine learning and deep learning techniques, as well as experience in generative modeling. The candidate will be responsible for designing, implementing, and optiizing generative models for a variety of applications, including natural language processing, computer vision, and audio processing.The candidate will also be responsible for analyzing and interpreting large datasets and communicating findings to both technical and non-technical stakeholders.
Responsibilities- Design, implement, and optimize generative models using machine learning and deep learning techniques.
- Apply generative models to a variety of applications, including natural language processing, computer vision, and audio processing.
- Analyze and interpret large datasets using statistical and machine learning technique.
- Communicate findings to technical and non-technical stakeholders.
- Collaborate with cross-functional teams to identify new opportunities for generative modeling.
Qualifications
0 to 2 years of experience in related field.
Strong background in machine learning and deep learning techniques.
Understanding of key concepts in the foundation models literature.
Experience in using/implementing/training/fine-tuning/optimizing foundation models or generative models.
Proficiency in programming languages such as Python or R.
Experience with deep learning frameworks such as TensorFlow or PyTorch.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Preferred Skills- Experience with natural language processing, computer vision, or audio processing generative models (including LLM, Diffusion models, GANs, VAEs..).
- Experience with deploying AI models at scale with frameworks such as FastAPI for API deployment, CI/CD for continuous integration and delivery and Docker/Kubernetes for containerization and scaling.
- Experience with cloud computing platforms such as AWS or Azure.