Chief Data Scientist | Machine Learning | Big Data

Chief Data Scientist | Machine Learning | Big Data

  • Location

    Oxford, Oxfordshire

  • Sector:

    Data Analytics & Artificial Intelligence

  • Job type:


  • Salary:

    £100000 - £150000 per annum

  • Contact:

    Michael Winter

  • Contact email:


  • Job ref:


  • Published:

    almost 2 years ago

  • Expiry date:


  • Startdate:



Oxford's most exciting consulting firm is looking for a Chief Data Scientist to join the growing team of specialists in their Oxford based office.
This is a young company, but it is full of seasoned experts spanning multiple different domains and varying expertise, all with one common goal - to use state of the art AI techniques and vast amounts of data to solve real world problems, specifically for construction and infrastructure metaprojects.

The ideal candidate will work with the team to solve big data, advanced analytics and machine learning related problems. You will need to bring data science expertise to a versatile set of problems to excel in this challenging but rewarding position.


  • Statistics
  • Machine Learning
  • Big Data
  • Programming
  • Management

Essential Skills & Background:

  • A PhD in Statistics or similar data-rich discipline from a top University
  • 1-3 years of relevant work experience working with and interrogating large Databases
  • Excellent statistical modelling and analytical background
  • Knowledge of one or more programming languages for data and analytics - R or Python.

  • Excellent communication skills, to both commercial, technical, and lay audiences. Good interpersonal skills; ability to work with colleagues at all levels.
  • Adept at using Microsoft Office products

Desirable Skills:

  • Scala and Tableau experience desirable


Data Science, Python, R, Statistics, advanced analytics, Machine Learning, Deep Learning, Consulting


  • Michael Winter | Michael.winter@wademacdonald.com | 01189559530 / 07825711262

Applications are encouraged from all candidates meeting or exceeding the minimum criteria for the role regardless of age, disability, gender, orientation, race, religion or ethnicity.