Data Scientist for Top Cosmetic firm
Toptal
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.