Data Science Manager

JOB   SUMMARY
At Publicis Sapient, we don’t just build technology; we create transformative solutions. By integrating Generative AI into our ecosystem, we’re shaping a new era of personalized and intelligent digital experiences for global clients. From building AI-driven content compliance systems to optimizing real-time decision-making, we leverage Large Language Models (LLMs) and cutting-edge AI technologies to solve industry-specific challenges.

Join us in driving innovation and delivering true business value to our customers through the strategic application of cutting-edge AI and data-driven solutions.

About the Team
The Data and AI Team at Publicis Sapient is at the forefront of AI innovation, crafting scalable solutions for enterprises across industries such as Healthcare, Retail, and Automotive. Our team blends expertise in data science, AI/ML, and software engineering to solve complex business challenges. By leveraging state-of-the-art Generative AI technologies, we create applications like intelligent content moderation engines, AI-driven recommendation systems, and LLM-based enterprise solutions.

About the Role
As a Manager Data Science specialising in Generative AI, you will:
Lead   AI-Driven   Innovations :
Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences.
Strategic

Collaboration:

Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data- driven solutions aligned with organizational goals.
Foster   a   High-Performance   Team :
Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning.
Deliver   Business   Impact :
Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP, ensuring measurable outcomes.
Optimize   AI   Pipelines :
Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real- time data processing challenges.
Customize   AI   Models :
Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain- specific requirements.
Promote   Data-Driven   Decision-Making :
Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact.
Develop   Intelligent   AI   Agents :
Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions.
Advance   Generative   AI   Applications :
Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation.
Scale   AI   with   Cloud   Technology :
Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency.
Stay   at   the   Cutting   Edge :
Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects.

Key Responsibilities
Design   AI   Systems :
Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization.
Develop   NLP   Pipelines :
Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation.
Integrate   Multi-Modal   Systems :
Combine data modalities such as text, images, and metadata for enriched user…