Назад
Company hidden
6 дней назад

Data Scientist

41 900 - 55 000GBP
Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Data Scientist (Machine Learning/Retail): Developing and deploying statistical, machine learning, and predictive models that turn complex consumer and retail data into actionable insights with an accent on scoring, model validation, and production readiness. Focus on exploring large datasets, building propensity and behavioural models, and monitoring scalable solutions in production.

Location: Stockport, United Kingdom

Salary: GBP 41,900–55,000 per year

Company

NIQ is a global consumer intelligence company providing data, technology, AI, and analytics solutions for consumer, retail, and technology businesses.

What you will do

  • Develop, test, validate, deploy, and monitor statistical, machine learning, and predictive models.
  • Explore large and complex datasets to identify patterns, opportunities, and suitable modelling approaches.
  • Build scoring solutions including propensity, classification, ranking, segmentation, and behavioural models.
  • Work with Data Scientists, Data Engineers, and business stakeholders on end-to-end solutions.
  • Translate model outputs into actionable scores, insights, and decision-support tools.
  • Maintain high-quality code and contribute to testing, documentation, peer review, and methodological improvements.

Requirements

  • 3–5 years of commercial data science experience.
  • Strong analytical, statistical modelling, and problem-solving skills.
  • Experience taking data science models from experimentation into production.
  • Experience with large-scale transactional, customer, product-level, FMCG, retail, or consumer behavioural data.
  • Understanding of cloud-based data and machine learning platforms, MLOps, model monitoring, and production lifecycle management.

Nice to have

  • Experience developing scoring, propensity, customer, classification, ranking, or behavioural models.
  • Experience with FMCG, retail, consumer purchasing, or behavioural datasets.
  • Experience with cloud-based data and machine learning platforms.

Culture & Benefits

  • Flexible working environment.
  • Volunteer time off.
  • LinkedIn Learning access.
  • Employee Assistance Program.
  • Collaborative work with Data Science, Engineering, and business teams.

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