Grundlæggende

Senior Data Scientist

manchester, north west england, United Kingdom Selskab: JR UK Klient / Arbejdsgiver: Harnham
Opslået: 19.05.2026
Afslutningsdato: 03.07.2026
Jobreference: 60aba665e51d918afe1944d9038cc45e

Jobinformation

Beliggenhed
manchester, north west england, United Kingdom
Selskab
JR UK
Klient / Arbejdsgiver
Harnham
Jobreference
60aba665e51d918afe1944d9038cc45e
Listetype
Grundlæggende
EU-arbejdstilladelse kræves
Nej
Opslået
19.05.2026
Afslutningsdato
03.07.2026

Jobbeskrivelse

Senior AI Engineer - Manchester or London

We are working on an exciting role with a scale up SaaS company who are focused on helping clients eliminate wasteful and fraudulent ad traffic.


The Role

We are looking for an experienced Data Scientist with strong ML & NLP expertise to build and improve models that detect invalid traffic (IVT) and protect ad spend. You’ll work with large-scale data, design production-ready ML systems, and collaborate closely with engineering to keep models performant and reliable.


Responsibilities

  • Develop and deploy ML models to detect bot and fraudulent traffic
  • Lead research and prototyping of new detection methods
  • Monitor model performance and address drift or false positives
  • Collaborate across teams to turn insights into product features
  • Ensure compliance, scalability, and reliability of ML systems

What We’re Looking For

  • Proven experience with ML in production environments
  • Strong skills in Python, SQL, and AWS (SageMaker, Lambda, etc.)
  • Experience with NLPs or LLMs
  • Familiarity with MLOps and real-time data applications
  • A pragmatic mindset and strong problem-solving ability
  • Background in adtech or fraud detection is a bonus

Færdigheder

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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