Основы

Lead Data Scientist

south west london, south east england, United Kingdom Компания: JR UK Клиент / Работодатель: Zazu Digital Talent
Опубликовано: 19.05.2026
Дата закрытия: 03.07.2026
Рекомендация по вакансии: a6c6a8219255c93a5476690c4eb180cc

Информация о вакансии

Расположение
south west london, south east england, United Kingdom
Компания
JR UK
Клиент / Работодатель
Zazu Digital Talent
Рекомендация по вакансии
a6c6a8219255c93a5476690c4eb180cc
Тип листинга
Основы
Требуется разрешение на работу в ЕС
Нет
Опубликовано
19.05.2026
Дата закрытия
03.07.2026

Описание должности

Founding Data Science Lead — (remote-first)

Confidential search · pre-Series A AI platform · live Fortune 500 traction


Three billion people now ask ChatGPT, Gemini and Google's AI Overviews every month what to buy, where to book and which brand is best. Our client is the AI platform that helps the world's biggest CPG brands measure, control and grow how they show up in those answers — and automates the actions that actually move sales.


This is not a pitch deck. They have paying enterprise customers live today (think household-name CPG, the kind whose logos are on every supermarket shelf), a strategic partnership in flight with a top-tier global consultancy, and founders with a prior MarTech exit track record on the commercial side and a scaled-platform principal-engineer pedigree on the technical side.


We're hiring the founding Data Science Lead.


You'll own: ranking, semantic search and recommendation systems; LLM behaviour modelling across ChatGPT, Gemini, Claude and AI Overviews; confidence scoring and generative-feedback evaluation of LLM outputs; the signal → action pipeline (turning unstructured content from Reddit, reviews, PDPs, YouTube and social into ranked, revenue-driving recommendations); entity resolution across Brand / Product-SKU / Retailer; knowledge graph (Neo4j / Neptune) + vector search (pgvector / Pinecone / Qdrant); and the full production ML lifecycle — including LoRA fine-tuning and RLHF / DPO alignment.


What we're looking for: 5+ years shipping production ML with measurable commercial impact; deep NLP, search / recommendation and retrieval experience; hands-on with modern LLM techniques; comfort with vector databases, knowledge graphs and messy multi-source data; early-stage temperament (no playbook, high autonomy, builder energy); and technical leadership that doesn't rely on the org chart.


You'll report to the CTO, work directly with the CEO, and set the ML foundations that thousands of brands will rely on to win in AI-driven discovery. Remote-first ideally from Portugal or the UK but flexible.


Pre-Series A, founding-team equity, a defined path to outcome.

Навыки

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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