Publicis Groupe accompagne les entreprises en communication, médias, marketing, données, technologie et transformation numérique, du conseil à la production.
Data Solutions Strategist, Applied AI
Company description Publicis Media harnesses the power of modern media through leading agency brands Dysrupt, Infinite Roar, Publicis Collective, Publicis Health Media, Spark Foundry, Starcom and Zenith, as well as global accelerator PMX; immersive experience group PMCI and access to integrated platform-based technologies and offerings from CJ, Epsilon and …
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Détails de l’offre
La description complète publiée par Publicis Groupe.
Description de l’offre
Company description Publicis Media harnesses the power of modern media through leading agency brands Dysrupt, Infinite Roar, Publicis Collective, Publicis Health Media, Spark Foundry, Starcom and Zenith, as well as global accelerator PMX; immersive experience group PMCI and access to integrated platform-based technologies and offerings from CJ, Epsilon and Influential. A key business solution of Publicis Groupe, Publicis Media’s digital-first, data-driven global solutions deliver client value and drive growth in a platform-powered world.
It is present in over 100 countries with over 23,000 employees worldwide. Overview We are looking for a Globally focused Data Solutions strategist to define how diverse data assets are integrated, governed, and activated through AI within Publicis AI solutions - as well as delivering actionable business and marketing intelligence.
Responsibilities
- Global Data Strategy: Define and evolve global data strategy for Publicis AI across media, transactional, attitudinal, identity, and external data sources.
- Data Framework Design: Establish strategic frameworks for how data is sourced, integrated, enriched, and activated to support AI-driven insights and decisioning.
- Technical Implementation & Deployment: Configure, build, test, and operationalize workflows across MRCL and supporting platforms. Support deployment readiness and ensure technical solutions can be adopted successfully by end users.
- AI & Product Alignment: Partner with AI, product, and engineering leaders to align data strategy with model development, GenAI use cases, and platform capabilities.
- Taxonomy & Signal Architecture: Lead the design of data taxonomies, ontologies, and signal frameworks that enable consistent intelligence across markets.
- Business Requirement Translation: Translate client and business objectives into data requirements that power marketing intelligence, measurement, and optimization.
- Governance & Responsible AI: Guide best practices for data governance, privacy, and responsible AI usage across global markets.
- Advisory & Enablement: Act as a strategic advisor to regional teams and clients on data readiness, data value, and AI enablement.
- Ecosystem Gap Identification
Qualifications
Ideal
Candidate Profile
- Deep understanding of how media, transactional, and attitudinal data combine to drive business and marketing intelligence.
- Proven ability to develop & communicate global data strategy across diverse markets/ stakeholders.
- Strong fluency in AI concepts and how data fuels ML, GenAI, and advanced analytics.
- Balances strategic vision with data availability, quality, & governance constraints
Qualifications
(Required)
- Relevant experience in data strategy, analytics strategy, or marketing intelligence.
- Expertise across media, transactional, attitudinal, and first-/third-party data ecosystems.
- Strong understanding of AI, machine learning, and advanced analytics strategies
- Experience working in global or multi-market environments.
- Proven ability to influence without direct authority in complex organizations. Preferred / Stand-Out Experience
- Experience leading or influencing enterprise or global data strategy initiatives
- Experience in media, marketing services, consulting, or technology platforms.
- Familiarity with identity resolution, measurement frameworks, or customer data platforms.
- Experience partnering with data science and engineering teams on AI initiatives.
- Background in developing data governance or responsible AI frameworks.
Additional information
Publicis Media offers a wide range of benefits to support our employees. Full details are shared when you join, but highlights include core benefits such as Pension, Life Assurance, and Private Medical cover, alongside enhanced policies like Reflection Days and Shared Parental Leave. You’ll also have access to a range of additional initiatives, including: 📖 Please check out the Publicis Career Page which showcases our Inclusive Benefits and our EAG’s (Employee Action Groups). Publicis Groupe works primarily from the office or our clients' office four days per week.
At Publicis Media, we are proud to be an equal opportunities employer. We welcome and encourage applications from people of all backgrounds, and do not discriminate on the basis of race, ethnicity, nationality, religion or belief, disability, age, citizenship, relationship status, sexual orientation, gender identity, or any other protected characteristic. We are committed to providing a fair, accessible, and inclusive recruitment process. If you have any access needs
- for example, related to disability, neurodivergence, or a health condition
- please let us know. We’ll work with you to ensure the process works for you. Sharing this information will never impact your application. Guided by our values, we listen with empathy, uplift each other, take responsibility, and embrace change
- building a culture where everyone feels seen, respected, and genuinely included.
- Global Data Strategy: Define and evolve global data strategy for Publicis AI across media, transactional, attitudinal, identity, and external data sources.
- Data Framework Design: Establish strategic frameworks for how data is sourced, integrated, enriched, and activated to support AI-driven insights and decisioning.
- Technical Implementation & Deployment: Configure, build, test, and operationalize workflows across MRCL and supporting platforms. Support deployment readiness and ensure technical solutions can be adopted successfully by end users.
- AI & Product Alignment: Partner with AI, product, and engineering leaders to align data strategy with model development, GenAI use cases, and platform capabilities.
- Taxonomy & Signal Architecture: Lead the design of data taxonomies, ontologies, and signal frameworks that enable consistent intelligence across markets.
- Business Requirement Translation: Translate client and business objectives into data requirements that power marketing intelligence, measurement, and optimization.
- Governance & Responsible AI: Guide best practices for data governance, privacy, and responsible AI usage across global markets.
- Advisory & Enablement: Act as a strategic advisor to regional teams and clients on data readiness, data value, and AI enablement.
- Ecosystem Gap Identification Ideal
Candidate Profile
- Deep understanding of how media, transactional, and attitudinal data combine to drive business and marketing intelligence.
- Proven ability to develop & communicate global data strategy across diverse markets/ stakeholders.
- Strong fluency in AI concepts and how data fuels ML, GenAI, and advanced analytics.
- Balances strategic vision with data availability, quality, & governance constraints
Qualifications
(Required)
- Relevant experience in data strategy, analytics strategy, or marketing intelligence.
- Expertise across media, transactional, attitudinal, and first-/third-party data ecosystems.
- Strong understanding of AI, machine learning, and advanced analytics strategies
- Experience working in global or multi-market environments.
- Proven ability to influence without direct authority in complex organizations. Preferred / Stand-Out Experience
- Experience leading or influencing enterprise or global data strategy initiatives
- Experience in media, marketing services, consulting, or technology platforms.
- Familiarity with identity resolution, measurement frameworks, or customer data platforms.
- Experience partnering with data science and engineering teams on AI initiatives.
- Background in developing data governance or responsible AI frameworks.
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