Senior Data Science Engineer

$134,000 - $161,000/Yr

Unclassified - Irving, TX

Full-time - Senior

Irving, TX

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 involves 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 required, along with exceptional ML engineering knowledge to manage complex ML workflows effectively. Candidates should have extensive experience in Data Science roles, with a proven track record of leading and mentoring small data science project teams. A successful history of taking multiple data science models and systems into production using the GCP ecosystem is necessary. Additionally, expertise in Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) is crucial, as well as familiarity with 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 model deployment.
• Mentor and lead small data science project teams.
• Manage complex ML workflows and ensure technical excellence in projects.
• Utilize GCP ecosystem tools for data science model deployment.

Requirements

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

Nice-to-haves

• Experience with prompt engineering and Retrieval Augment generation.
• Ability to work with large datasets and preprocessing techniques.
• Experience in building 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.