Data Scientist

Remote, Great Britain, United Kingdom

Applications have closed

About EDITED

EDITED is the global leader in Retail Intelligence. We help retailers increase margins, generate more sales and drive better outcomes through AI-driven Automation and Market & Enterprise Intelligence.

By connecting internal enterprise and external market data, brands like John Lewis and Puma use the EDITED suite of intelligence products to drive insights into action in a more profitable and coordinated way.

At EDITED, we always dream big, with a commitment to deliver measurable value to our customers. We believe in exceeding expectations and challenging the status quo. We do so by delivering our powerful Retail Intelligence Platform that drives better and faster decision making for retailers.

We are a remote-first company, which means you can work fully remotely or from one of our offices.

The Team

At EDITED, you’ll be part of our Product and Engineering team, working closely with other software developers and data scientists, retail specialists and designers to create data-driven solutions to our customers' problems. We've got huge scope to innovate and we always welcome fresh perspectives. You'll be able to make a big impact, and learn a huge amount during your time at EDITED.

The Job

The EDITED data team is responsible for augmenting our data using machine learning and data mining techniques to categorise products, understand trends, predict future behaviours and correlate information across datasets. Working with one of the largest fashion databases globally, the team utilizes all data available to derive insights and create products in the apparel market.

Responsibilities:

  • Development and maintenance of Machine learning models in a production environment.
  • Data Analysis and presentation of complex technical concepts to provide both internal and external insights to key stakeholders.
  • Development of tools and processes to optimise ETL processes for our big data pipeline
  • Presentation of complex technical concepts to key stakeholders
  • Research state of the art ML models and apply them to our use cases

Requirements

Essential:

  • 1+ years of experience as a Data Scientist or similar in a commercial setting
  • Masters Degree in Quantitative field e.g. Statistics, Mathematics, Computer Science or Economics or higher
  • Commercial experience of researching and applying machine learning techniques
  • Experience with ETL
  • Experience with programming Python, R or SQL
  • A collaborative, friendly approach, a constructive viewpoint and a team player
  • Ability to articulate complex ideas concisely
  • A problem solver with an analytical mindset
  • A great communicator - you can explain statistical significance to a manager, a software engineer, or a retail buyer

Bonus Points:

  • Experience with large-scale analysis components such as AWS and Spark or column stores such as Elasticsearch or Postgres
  • Have experience in finding insights from large scale data sets
  • Experience with data visualisation tools (e.g. Tableau)
  • Experience working with cutting edge, image-based ML models

Benefits

  • If you’re a working parent, you can utilise our flexible working policy to ensure you can work around your schedule - this means starting + finishing when it suits you best!
  • We are remote-first, which means you can work fully remotely, from one of our offices, or a bit of both - the choice is yours
  • Enhanced parental leave policy
  • Flexibility and understanding for big life events like the first day of school or school sports day
  • 25 days annual leave + public holidays (and an extra day for every year at EDITED)

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: AWS Big Data Computer Science Data analysis Data Mining Economics Elasticsearch Engineering ETL Machine Learning Mathematics ML models PostgreSQL Python R Research Spark SQL Statistics Tableau

Perks/benefits: Career development Flex hours Parental leave Salary bonus Team events

Regions: Remote/Anywhere Europe
Country: United Kingdom
Job stats:  10  2  1
Category: Data Science Jobs

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