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обновлено 26 дней назад

Junior Data Scientist

Формат работы
onsite
Тип работы
fulltime
Грейд
junior
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
Junior Data Scientist (Python/SQL): Building and maintaining data science models and production pipelines for ecommerce marketing measurement with an accent on attribution, forecasting, incrementality testing, and model backtesting. Focus on systematically debugging unfamiliar codebases, reviewing AI-assisted production code, validating AWS pipelines, and explaining methodology and findings to clients and colleagues.

Location: London, United Kingdom

Company

hirify.global builds marketing measurement products for ecommerce brands, including attribution, marketing mix modelling, incrementality testing, and brand impact measurement.

What you will do

  • Own moderately difficult tickets from analytical investigations and model backtesting to production bug fixes and pipeline work.
  • Systematically debug partly unfamiliar codebases using AI tooling to accelerate investigations.
  • Write and review production Python and SQL while avoiding technical debt.
  • Use QA automation and AWS data science pipeline tooling effectively.
  • Explain methodology and findings to clients and colleagues.
  • Clarify acceptance criteria and become an internal data science contact for owned areas.

Requirements

  • 1–2 years of commercial data science experience or a strong placement/internship record alongside a quantitative degree.
  • Strong Python and SQL skills with experience collaborating on shared code.
  • Deep knowledge of several machine learning algorithms and when to apply them.
  • Ability to systematically debug unfamiliar code and independently complete scoped work.
  • Strong AI fluency, including reviewing AI output for accuracy and brevity.
  • Clear communication, attention to detail, critical thinking, and initiative.

Nice to have

  • Experience with AWS or comparable cloud tooling.
  • Familiarity with automated QA tooling and test coverage practices.
  • Experience with marketing, ecommerce, or advertising data.
  • Exposure to Bayesian methods, marketing mix modelling, or experimental design.

Culture & Benefits

  • Published six-level Data Science Career Development Framework with explicit progression criteria.
  • Regular code review and methodology critique focused on model quality.
  • Supportive team structure with progressively increasing ownership.
  • Direct impact on budget decisions through models used by recognizable brands.

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