Decision Scientist

Aspire Data Recruitment
17 May 2017
16 Jun 2017
Contract Type
Full Time

Job Title: Decision Scientist

Location: London

Salary: £30,000 - £50,000

This role offers a chance to shape the Decision Science team’s future, including:

  • Defining the quantitative element of projects, for internal R&D and for external clients;
  • Contributing to the choice of quantitative & analytical techniques used to deliver projects;
  • Quantitative input into the design and testing of prototype concepts for full solution implementation;
  • Reviewing the latest mathematical trends and opportunities for method transfer and adoption / inclusion;
  • Contributing to proposals, as a subject matter expert on applied analytics and innovative techniques;
  • Communicating with both staff and clients in technical and non-technical terms language.

The following areas summarise the knowledge they are looking for:

  • Extensive understanding of mathematics and its practical application to problem solving;
  • Insight and opinion on leveraging data, through analytics and creative interpretation to deliver actionable insight;
  • A perspective on past, present and future trends in mathematics and computer sciences and opportunities for technology transfer;
  • Knowledge of big data platforms and numerical analysis methods for processing optimisation;
  • Some experience in handling and integrating qualitative data sets such as social network data, questionnaires, surveys;
  • Creative ideas for the presentation and visualisation of data and insight.

Success will ultimately be enabling the team to move forward at increasing pace to achieve these, you should be able to:

  • Develop practical/pragmatic mathematical solutions from first principles using coding languages such as C/C++/Java, Python, Fortran;
  • Select fit for purpose mathematical/statistical approaches using third party toolkits such as, but not limited to, Mathematica, Matlab, SAS, SPSS, R;
  • Apply a range of techniques and theories from mathematics, statistics, decision science, data engineering, data warehousing and visualisation to extract meaning from complex, unstructured data;
  • Communicate ideas clearly and concisely, whether verbally, through intuitive software or documentation, to craft an appropriate story for a non-technical audience;
  • Adapt and learn quickly from SMEs, functional and industry experts, to acquire good process knowledge of client operations, functions and challenges;
  • Plan your time effectively and deliver multiple projects to time and budget;

You are likely to have recently acquired a PhD in a numerical discipline such as applied or pure mathematics, statistics, physics or computer science and perhaps gained early experience in your first role or post-doctoral research in an academic institute.