Manager Data Science

Descrizione del lavoro:

Company description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting, and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of the next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients' businesses through designing the products and services their customers truly value. Overview As a Manager for Data Science consulting, you operate at the intersection of business strategy, data, and emerging AI technologies. You work closely with clients to shape their data and AI agendas-translating business challenges into actionable opportunities, advising on the right approaches, and guiding initiatives from idea through to value realization. You bring a strong technical foundation, but your primary focus is on understanding client needs, framing problems, and designing impactful solutions. You are a trusted advisor who can connect strategy, data, technology, and organizational change-while staying hands-on enough to explore data, prototype solutions, and leverage modern AI tools. Responsibilities Shape Data & AI Strategy Partner with clients to define their data and AI vision, identify high-value use cases, and translate business goals into actionable roadmaps. Engage and Advise Stakeholders Lead conversations with business and technical stakeholders to uncover requirements, challenge assumptions, and guide decision-making on AI and data science initiatives. Translate Business Problems into Solutions Frame complex business challenges into structured analytical or AI-driven approaches, selecting the right methodologies, tools, and architectures. Explore and Prototype Drive innovation by evaluating and applying emerging AI technologies and methodologies, ensuring Publicis Sapient remains at the forefront of data science advancements. Stay close to the technology-exploring datasets, building lightweight prototypes, and leveraging modern AI tools (e.g., LLMs, copilots, automation frameworks) to validate ideas and accelerate delivery. Bridge Business and Technology Work across disciplines (engineering, product, design) to ensure solutions are feasible, scalable, and aligned with business needs. Drive AI Adoption and Innovation Evaluate emerging technologies and help clients adopt AI in a practical, value-driven way-extending beyond traditional data science into areas such as generative AI, automation, and decision intelligence. Communicate Impact Clearly articulate insights, recommendations, and trade-offs to both technical and non-technical audiences, including senior leadership. Contribute to Growth and Capability Building Support business development, shape proposals, and mentor team members-fostering a culture of curiosity, learning, and innovation Qualifications Strong experience in data, AI, or analytics roles, with exposure to both technical implementation and business-facing work Proven ability to engage clients, structure problems, and translate business needs into data/AI solutions Proven experience in developing and deploying AI models at scale, including natural language processing (NLP), computer vision, and reinforcement learning. Expertise in machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud-based AI platforms (e.g., AWS, GCP, Azure). Strong understanding of data engineering concepts, including data pipelines and big data technologies such as Spark, Hadoop, SQL, and NoSQL. Experience working with modern AI ecosystems (e.g., cloud platforms, LLMs, AI tools, or data platforms) Strong communication and storytelling skills, with the ability to influence stakeholders at multiple levels Comfortable working in ambiguous environments, exploring new problem spaces, and expanding into adjacent domains Demonstrated curiosity and eagerness to learn and apply new technologies, especially within the rapidly evolving AI landscape Experience in consulting, digital transformation, or cross-functional environments is a strong plus Additional information Set Yourself Apart With Experience defining AI or data strategies for organizations Hands-on experience with modern AI tools (e.g., generative AI, copilots, automation platforms) Exposure to data architecture, data engineering, or product development Track record of driving AI adoption or innovation initiatives within organizations Advanced degree in a relevant field (e.g., data science, engineering, business, or similar) What We're Looking For We're looking for someone who is: Equally comfortable in the boardroom and with a dataset A translator between business ambition and technical reality Curious, adaptable, and excited about the fast-moving AI landscape Motivated to go beyond pure data science into broader problem-solving and innovation

Requisiti del candidato:

Strong experience in data, AI, or analytics roles, with exposure to both technical implementation and business-facing work Proven ability to engage clients, structure problems, and translate business needs into data/AI solutions Proven experience in developing and deploying AI models at scale, including natural language processing (NLP), computer vision, and reinforcement learning. Expertise in machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud-based AI platforms (e.g., AWS, GCP, Azure). Strong understanding of data engineering concepts, including data pipelines and big data technologies such as Spark, Hadoop, SQL, and NoSQL. Experience working with modern AI ecosystems (e.g., cloud platforms, LLMs, AI tools, or data platforms) Strong communication and storytelling skills, with the ability to influence stakeholders at multiple levels Comfortable working in ambiguous environments, exploring new problem spaces, and expanding into adjacent domains Demonstrated curiosity and eagerness to learn and apply new technologies, especially within the rapidly evolving AI landscape Experience in consulting, digital transformation, or cross-functional environments is a strong plus