Senior Data Science Engineer

$134,000 - $161,000/Yr

Unclassified - New York, NY

Full-time - Senior

New York, NY

10,001+ employees

About the position

The Senior Data Science Engineer at Publicis Sapient plays a pivotal role in driving data-driven transformations (DDT) for clients globally. This position is designed for individuals who are passionate about leveraging machine learning and artificial intelligence, particularly generative AI, to solve real-world problems. The Senior Associate will collaborate closely with digital directors, client teams, and practice capabilities to accelerate and implement DDT strategies effectively. This role is crucial in ensuring that Publicis Sapient remains an industry leader in digital thinking, execution, and value realization through innovative data-driven solutions. In this position, the Senior Data Science Engineer will be responsible for developing and implementing generative AI models and algorithms, including Retrieval Augment generation and prompt engineering. Candidates should possess the ability to work with large datasets and have a strong understanding of preprocessing techniques. Experience in building and deploying multi-modal generative AI systems in real-world applications is essential, along with familiarity with the GCP ecosystem, particularly ImageGen, Vector Search, and Vertex AI. The role also requires leading the development and implementation of advanced machine learning models, ensuring high standards of technical excellence. The Senior Associate will design and implement ML engineering workflows, streamlining the deployment of models and systems to production for optimal efficiency. A strong understanding of machine learning and deep learning principles is necessary, as well as exceptional ML engineering knowledge to manage complex ML workflows effectively. Additionally, the candidate should have extensive experience in Data Science roles, with a proven track record of leading and mentoring small data science project teams. The ability to successfully take multiple data science models and systems into production using the GCP ecosystem is crucial. Familiarity with Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) is also required, along with expertise in collaborative development tools and practices, including peer code reviews and version control (Git).

Responsibilities

• Work with clients to drive data-driven transformation strategies.
• Develop and implement generative AI models and algorithms.
• Collaborate with digital directors and client teams to ensure successful project execution.
• Lead the development and implementation of advanced machine learning models.
• Design and implement ML engineering workflows for optimal efficiency.
• Mentor and lead small data science project teams.
• Take multiple data science models into production using the GCP ecosystem.
• Manage complex ML workflows and ensure technical excellence.

Requirements

• Extensive experience in Data Science roles with a focus on machine learning and AI.
• Proven background in leading and mentoring data science project teams.
• Experience in developing and implementing generative AI models and algorithms.
• Strong understanding of machine learning and deep learning principles.
• Familiarity with GCP ecosystem, including ImageGen, Vector Search, and Vertex AI.
• Expertise in Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps).
• Proficiency in collaborative development tools and practices, including Git.

Nice-to-haves

• Experience with Retrieval Augment generation and prompt engineering.
• Ability to work with large datasets and understand preprocessing techniques.
• Experience in building and deploying multi-modal generative AI systems.

Benefits

• Flexible vacation policy; time is not limited, allocated, or accrued.
• 16 paid holidays throughout the year.
• Generous parental leave and new parent transition program.
• Tuition reimbursement.
• Corporate gift matching program.