Ds for Top Cosmetic Firm

**Summary** We are seeking a Data Scientist to analyze anonymized consumer interaction data and uncover patterns in unstructured language across call center and cross-channel conversations. The primary goal is to identify intent, surface trends, and turn language into structured insights that can inform content strategy and web experiences. **General information** This engagement focuses on a large historical dataset collected over 10 years across consumer information and interaction touchpoints. The data includes call center and cross-channel interactions, with existing KPI reporting around areas such as conflict types and call duration, but limited analysis of the underlying unstructured language. The data sits in a homegrown database and Azure environment, with an anonymized semantic layer. The initial phase will be exploratory and somewhat open-ended, starting with manual exports of conversation data before more connected pipelines are established. This role will work closely with a Program Manager supporting the broader effort. **Tasks and Deliverables** \- Analyze anonymized consumer interaction and call center conversation data. \- Review exported conversation data across channels, brands, and interaction types. \- Identify intent patterns within unstructured language and conversation content. \- Spot trends in customer language not captured by existing KPI reporting. \- Convert unstructured language into structured insights and usable analysis frameworks. \- Develop recommendations on how findings can inform content strategy. \- Explore how LLM-era language analysis can support web content decisions. \- Collaborate closely with the paired Program Manager on analysis priorities and outputs. **Required experience** \- Proven experience as a Data Scientist working with large-scale datasets. \- Strong experience analyzing unstructured text or language-based data. \- Experience identifying trends, patterns, and intent signals from customer interactions. \- Ability to translate exploratory analysis into structured, actionable insights. \- Experience working with anonymized or sensitive consumer data. \- Familiarity with Azure-based data environments. **Engagement highlights** \- Opportunity to shape the first meaningful language analysis of a rich 10-year dataset. \- High-ownership engagement with room to define the analytical approach. \- Direct impact on how customer language insights inform content and web strategy.