핵심 요구사항
- 대규모 데이터셋을 다룬 데이터 사이언티스트 경력
- 비정형 텍스트/언어 데이터 분석 역량
- 고객 상호작용에서 의도·트렌드·패턴 도출 경험
- 탐색적 분석을 구조화된 실행 가능 인사이트로 변환하는 능력
- 익명화/민감 소비자 데이터 취급 경험
- Azure 기반 데이터 환경 친숙도
Required stack
필요 기술
AzurePythonNLPLLMData Science
Project brief
프로젝트 내용
Headquarters:
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.
To apply: https://weworkremotely.com/remote-jobs/toptal-data-scientist-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.
To apply: https://weworkremotely.com/remote-jobs/toptal-data-scientist-for-top-cosmetic-firm
지원 기회 분석
지원 전에 볼 것
예상 산출물
- 비정형 대화 데이터의 의도 패턴 분석 결과
- 기존 KPI가 포착하지 못한 고객 언어 트렌드 리포트
- 구조화된 인사이트 및 분석 프레임워크
- 콘텐츠 전략에 적용할 권장 사항
매력 포인트
- 10년치 풍부한 데이터의 첫 언어 분석을 주도하는 기회
- 높은 자율성과 분석 방향 정의 권한
- Toptal 경유의 검증된 대형 클라이언트
확인할 점
- 예산·기간 미명시
- 초기 단계가 개방적이고 스코프가 불명확(수동 데이터 추출부터 시작)
Client signal
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