Overview:
The Commercial Data & Personalization Lead is primarily accountable for building and managing the data infrastructure and personalization capabilities that enable the team to deliver targeted, data-driven customer experiences at scale. Sitting at the intersection of data engineering and growth, this role combines hands-on technical development with a strong commercial lens — ensuring that the data products and tools built are directly tied to business outcomes such as customer lifetime value growth, engagement, and revenue optimization. This person works closely with cross-functional engineering and data science teams to develop and operationalize solutions, rather than operating in isolation.
What you will do:
- Designing and developing data features that power personalization and customer targeting — such as customer segmentation, behavioral enrichment, interest profiling, and location-based data structuring — with a clear line of sight to how they drive growth outcomes
- Building and maintaining end-to-end data pipelines that transform raw data into actionable inputs for campaign orchestration, personalization engines, and recommendation systems — in close collaboration with engineering and data science teams
- Managing customer data platforms and tooling — including segment definitions, data ingestion, and real-time data availability — ensuring downstream teams and systems have access to accurate and timely data
- Owning the configuration and optimization of personalization platforms and content management systems — managing targeting rules, placements, and personalization logic that shape customer-facing experiences
- Collaborating with data science teams to ensure clean, enriched, and well-structured data flows into model development — supporting recommender systems, predictive models, and experimentation use cases
- Providing the data foundation for growth experimentation — setting up test/control frameworks, measurement pipelines, and tracking infrastructure that enable the team to rapidly test and scale personalization hypotheses
What we are looking for:
- 3–5 years of experience in data, analytics, growth, or related roles, ideally within a product, marketing, or commercial team environment
- Working knowledge of data tools and concepts(e.g., SQL, Python, or similar), with the ability to understand, explore, and work with structured datasets—hands-on depth is a plus
- Experience working with customer data platforms, personalization tools, or marketing technology stacks
- Experience contributing to data-driven initiatives (e.g., building datasets, supporting pipelines, or enabling reporting/targeting use cases), with a practical understanding of how data products support business needs
- Strong commercial awareness—ability to connect technical work to business outcomes such as revenue growth, customer engagement, and lifetime value
- Experience collaborating with cross-functional engineering, data science, and product teams
- Familiarity with experimentation frameworks and A/B testing infrastructure is a plus
- College graduate. Preferably a degree in computer science, data science, engineering, statistics, or related courses
