Junior Data Scientist

Haystack

Data SciencejuniorLondon Area, United KingdomonsitefulltimeTechnology, Information and MediaPythonSQLmachine learning algorithmsBayesian attributionMMM (Marketing Mix Modeling)causal inferenceposted 15 Sep
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We're hiring for a leading provider of measurement solutions for online retail, empowering teams with full-funnel marketing insights, forecasting, and optimization. This company is dedicated to helping businesses move faster and grow smarter through advanced data analytics.

The Role

  • Own moderately difficult data science tasks end-to-end, including analytical investigations, model backtesting, and production bug fixes.
  • Systematically debug code across various repositories, leveraging AI tooling for efficiency.
  • Write and review production-level Python and SQL code, focusing on quality and minimizing technical debt.
  • Effectively utilize cloud tooling and QA automation for data validation and pipeline understanding.
  • Communicate methodologies and findings directly to clients and colleagues.
  • Proactively collaborate with other teams to define requirements and acceptance criteria.
  • Develop into an internal data science champion for owned areas.

What You'll Need

  • 1-2 years of commercial data science experience or a strong academic record with a quantitative degree.
  • Strong proficiency in Python and SQL, with experience in collaborative coding environments.
  • Deep understanding of a select few machine learning algorithms and their appropriate applications.
  • Demonstrated ability to systematically debug unfamiliar codebases, with effective use of AI assistance.
  • Strong AI fluency, understanding how to optimally leverage AI tools for task initiation and dependency resolution.
  • Confidence in completing work independently once scope is agreed upon.
  • Ability to communicate effectively with stakeholders with minimal supervision.
  • Genuine attention to detail, with a keen eye for identifying inaccuracies.

What's On Offer

  • Competitive salary
  • A published Data Science Career Development Framework with clear progression criteria.
  • Opportunities to work on advanced methodologies like Bayesian attribution, MMM, and causal inference.
  • A collaborative team environment with rigorous code and methodology reviews.