{"id":3022,"date":"2026-08-11T13:28:14","date_gmt":"2026-08-11T13:28:14","guid":{"rendered":"https:\/\/tradefinder.help\/?p=3022"},"modified":"2026-08-11T13:28:14","modified_gmt":"2026-08-11T13:28:14","slug":"toptal-data-scientist-for-top-cosmetic-firm","status":"publish","type":"post","link":"https:\/\/tradefinder.help\/?p=3022","title":{"rendered":"Toptal: Data Scientist for Top Cosmetic firm"},"content":{"rendered":"

\n Headquarters:<\/strong>\n<\/p>\n

Summary<\/strong>
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.<\/p>\n

General information<\/strong>
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.<\/p>\n

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.<\/p>\n

<\/p>\n

Tasks and Deliverables<\/strong>
– 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.<\/p>\n

Required experience<\/strong>
– 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.<\/p>\n

Engagement highlights<\/strong>
– 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.<\/p>\n

To apply:<\/strong> https:\/\/weworkremotely.com\/remote-jobs\/toptal-data-scientist-for-top-cosmetic-firm<\/a><\/p>","protected":false},"excerpt":{"rendered":"

Headquarters: SummaryWe 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 informationThis engagement focuses on a large […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3022","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"featured_image_url":[],"post_author":"sonifashionhouse@gmail.com","assigned_categories":"Uncategorized","jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/tradefinder.help\/index.php?rest_route=\/wp\/v2\/posts\/3022","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tradefinder.help\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tradefinder.help\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tradefinder.help\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tradefinder.help\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3022"}],"version-history":[{"count":0,"href":"https:\/\/tradefinder.help\/index.php?rest_route=\/wp\/v2\/posts\/3022\/revisions"}],"wp:attachment":[{"href":"https:\/\/tradefinder.help\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3022"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tradefinder.help\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3022"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tradefinder.help\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3022"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}