Data Scientist – London

About the Job

Company

Sandtable is a data science company that creates simulations of human behaviour to support strategic decision making by organisations.

Role

To build insight (understanding why) and foresight (understanding what if) into human behaviour through data analysis and the development of data-driven computational models

Job description

  • Work closely with the planning team to identify and answer client questions
  • Answer client questions by using appropriate statistical / modelling techniques on available data
  • Conduct exploratory data analysis on a wide rage of data sets
  • Communicate findings clearly
  • Drive the collection of new data and the refinement of existing data sources, cleaning, processing and re-organising data as necessary.
  • Build data-driven computational simulations to predict and understand behaviour.
  • Analyze and interpret the results of model-based experiments
  • Develop novel metrics for model evaluation and exploration
  • Work with the visualisation team to design and create engaging and useful applications to explore model output data

Skills, qualifications & experience

  • Ph.D. in a physical, biological or engineering science
  • 1+ years experience using Agent Based Modelling (ABM)
  • 3+ years experience working with large volumes of real data
  • Programming competence in Python
  • High level of expertise in statistics (frequentist and Bayesian)
  • Familiarity with relational databases and SQL (3+ years)
  • Experience with machine learning techniques, in particular clustering (1+ years)
  • Experience working with cloud based systems, specifically AWS, and data science tools such as Redshift
  • Experience manipulating and analysing dirty, complex, high-volume, high-dimensionality data from varying sources
  • An interest in underlying domain problems (not just model maths)
  • Extensive experience solving analytical problems using quantitative approaches
  • A passion for empirical research and for answering hard questions with data
  • A flexible analytic approach that allows for results at varying levels of precision
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner