Robert Walters

Data Scientist

Job description

Our data scientists employ advanced mathematics, statistics, and computer science (ML and algorithmic), to tackle complex business problems. The Data Scientist should have a pragmatic approach to problem-solving and be capable of developing solutions to rely on in production. They should be capable of challenging their own work, and of finding balance between perfection and practicality.

Qualifications and Experience

  • Educated to degree level within a technical discipline
  • Experience in a Data Science role at both proof-of-concept and production stages
  • Proficient in Python and SQL-like language
  • Confident at data wrangling/cleaning in a dataframe package (e.g. Python’s pandas)
  • Knowledge of general ML concepts (training/test, cross-validation, supervised/unsupervised learning, regression and classification, clustering, over/under-fitting, accuracy/precision/recall, ensemble methods, dimension reduction and feature extraction)
  • For at least a few specific models—e.g. trees, forests, neural networks, gradient boosting, SVMs, k-means… though not necessarily all of these—to know how they actually work, algorithms involved, etc.
  • Reasonable knowledge of fundamental computer science concepts (time/space complexity, hashing, simple algos for sorting/searching/etc.)
  • Able to work with linux/*nix systems, bash scripting, SSH with minimal instruction
  • Experience developing modularised code, using version control with git—other DevOps knowledge, such as containerisation using Docker, highly desirable
  • Ideally, familiarity with an ML framework like Torch or TensorFlow
  • Ideally, familiarity with a distributed framework like Spark


Our data scientists employ advanced mathematics, statistics, and computer science (ML and algorithmic), to tackle complex business problems.The Data Scientist should have a pragmatic approach to problem-solving and be capable of developing solutions to rely on in production ...

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