Data Scientist, Creative Excellence

Data Scientist – Creative Excellence (Ipsos, US)

Within Ipsos, the Creative Excellence Service Line helps clients understand what makes advertising effective across TV, digital, social and other media channels. A core strategic solution is Creative Spark AI, an AI‑enabled capability to predict and explain ad performance at scale and globally. Your primary focus will be to support the development and evolution of this solution, including the creation of new products that leverage the framework to capture current blue‑ocean opportunities.

• Opportunity to work with cutting‑edge AI and data technologies in a production environment alongside experienced data scientists and engineers.
• Culture that values curiosity, scientific rigor, collaboration and continuous learning.
• Chance to grow towards senior or specialized roles (lead data scientist, AI product specialist, domain expert in creative analytics).

Design, experiment and iterate AI models and features that power Creative Spark AI and related solutions. Translate research and client briefs into modeling problems, ensuring actionable insights and recommendations. Work autonomously on well‑defined problems, collaborating closely with lead data scientists and engineers, and progressively take ownership of complex modeling work streams.

• Feature and Model Development – design, engineer and test new model variants from survey, coded or digital data sources to improve prediction accuracy and explainability across distinct ad environments and verticals.
• Integrate new features into experimental models, quantify their impact and summarize the uplift (or lack thereof) for senior management decision‑making.
• Document feature definitions, derivation logic and performance impact for replicability.
• Experimentation, Evaluation & Documentation – design and execute experiments and benchmarks comparing different feature sets, algorithms or model configurations (classical ML, deep learning, NLP/CV approaches).
• Use appropriate evaluation metrics (accuracy, AUC, RMSE, calibration, stability across segments) and validation schemes (cross‑validation, hold‑out, time‑based splits).
• Maintain clear experiment logs and documentation (notebooks, reports, dashboards) so results can be reviewed, reproduced and reused by CRE and GADS teams.
• Advocate for and own new products and solutions that grow incremental revenue on top of CRE’s core business.
• Translate understanding of Ipsos’ Creative Excellence business into new solutions in collaboration with global and US product teams.
• Enhance insight generation, augmenting traditional data methods and enabling advanced market simulations.
• Support innovative product development, new revenue streams and greater value from data assets.
• Help translate stakeholder business and research questions into robust, documented analytical workflows aligned with Ipsos’ methodologies and AI governance.
• Present modeling results, feature impacts and recommendations in clear, non‑technical language to CRE stakeholders.
• Collaborate with business‑facing teams to frame and refine client questions, ensuring feasibility and methodological rigor.
• Contribute to internal training, playbooks and knowledge sharing on our core AI solution.

• Master’s degree (or equivalent) in Data Science, Statistics, Applied Mathematics, Computer Science, Econometrics or related quantitative field.
• PhD is a plus but not required.

• 7–10 years of professional experience as a Data Scientist in applied machine learning.
• Hands‑on experience building and evaluating supervised learning models (regression / classification) in real‑world use cases.
• Experience in product management or technical lead roles is a plus.
• Experience in at least one of the following:
  • Marketing, advertising, media or market research.
  • Predictive modeling on survey, panel or customer behavior data.
• Prior exposure to production or near‑production environments (e.g. models that are deployed, monitored and iterated).

• Strong proficiency in Python and the main data & ML libraries (pandas, Num Py, scikit‑learn, Tensor Flow, PyTorch,…