Consultant - Data Scientist (Retail Media experience)

Role Purpose:

Retail Data Scientist (Retail Media Specialist)

Key Responsibilities:

1. Data Science & Machine Learning for Retail

• Develop and deploy

  AI/ML models

  for retail media and commerce use cases such as:
  • Customer segmentation and lookalike modeling
  • Ad targeting and campaign optimization
  • Multi-touch attribution and marketing mix modeling
  • Recommendation systems and personalization
  • Retail media ROI measurement and bidding optimization
• Analyze 1P (retailer-owned), 2P, and 3P data to drive actionable insights.
• Apply advanced techniques (predictive modeling, clustering, NLP, deep learning) to solve complex business problems.

2. Retail Media Analytics

• Design and implement analytical frameworks for

  retail media networks

  helping retailers monetize audience data through digital advertising.
• Build data pipelines and models that measure campaign performance and optimize media spend.
• Partner with retail clients to define KPIs for advertising effectiveness, conversion uplift, and category growth.
• Work with data from media platforms (Google Ads, Meta, Amazon Advertising, Trade Desk, Criteo, etc.).

3. Business Consulting & Client Delivery

• Translate business challenges into data science solutions that align with client objectives.
• Collaborate with global retail and media experts to co-create AI-based solutions.
• Present technical findings in a clear, business-focused way to senior stakeholders.
• Support project planning, execution, and delivery across multi-market engagements.

4. Technical Enablement & Collaboration

• Work with data engineers and architects to ensure scalable model deployment and integration.
• Utilize cloud platforms (Azure, AWS, or GCP) for model training and deployment.
• Contribute to reusable AI accelerators, frameworks, and assets within the global network.

5. Innovation & Knowledge Building

• Research and implement emerging AI and retail media trends such as

  clean rooms, identity resolution, generative AI for ad content

  , and

  real-time personalization

  .
• Develop PoCs and contribute to thought leadership (whitepapers, playbooks, or case studies).

Qualifications & Skills:

Education:

• Bachelors or Masters degree in Data Science, Computer Science, Statistics, Economics, Engineering, or related field.
• Ph.D. preferred (optional) for advanced analytical modeling roles.