The client, a large restaurant brand, is undergoing a multi-year digital transformation focused on growth, personalization, and loyalty. They need to modernize their customer experience and technology stack by leveraging data-driven decision-making and AI/ML to fuel their growth strategy.
Requirements
- Experience developing and deploying production-grade ML models in cloud environments (AWS, GCP, or similar).
- Deep expertise in statistical modeling, machine learning, experimentation, and predictive analytics.
- Strong technical fluency with Python, SQL, Spark, cloud data platforms, and modern ML frameworks.
- Experience with pricing elasticity, customer lifetime value modeling, loyalty and CRM analytics, or personalization engines.
- Familiarity with tools such as SageMaker, GitHub, Databricks, or similar modern ML ops stacks.
Responsibilities
- Build, manage, and mentor a team of data scientists, ML engineers, and analysts while fostering a culture of experimentation and technical excellence.
- Develop predictive, prescriptive, and generative AI models that unlock value across loyalty, CRM, pricing, traffic forecasting, and customer lifetime value optimization.
- Create scalable measurement and modeling frameworks for pricing elasticity, promotional lift, personalization, and omni-channel engagement.
- Oversee deployment of production-level models and ensure governance, model monitoring, and lifecycle management best practices.
- Drive executive thought leadership on AI/ML maturity, experimentation, and data science investment strategy.
- Champion ethical AI practices and advocate for data quality, platform standardization, and cloud-native scalability.
Other
- Define and lead the enterprise data science strategy aligned to commercial, marketing, digital, and operations priorities.
- Partner with marketing, product, digital, and finance leadership to embed analytics into business decisioning and enterprise dashboards.
- Serve as a strategic advisor to C-suite stakeholders, translating complex analytics into clear recommendations that influence business outcomes.
- Proven track record building and scaling enterprise data science functions with measurable business impact.
- 15+ years of experience in data science, advanced analytics, or machine learning, including 3+ years building and leading high-performing teams.
- Experience applying analytics in a large-scale consumer, retail, eCommerce, or QSR environment.
- Executive-level communication skills with the ability to influence strategy at the highest levels of the organization.
