Datatech Analytics

Associate Data Scientist

Job description

Associate Data Scientist * London * £Competitive * J11792

Due to rapid growth a leading global consultancy have opened up an exciting new position for a Data Scientist in the Analytics Team to strengthen and advance the use of data and insight across business functions and external client bases. The role will require someone who has a very strong data modelling background, experience of using Python, R, Alteryx, Stata and SQL.

  • To use in-depth knowledge of analytical methods to problem-solve
  • Take ownership of propensity models for key customers and demographics
  • Develop and productionise models quantifying property characteristics and market performance
  • Develop machine learning approaches which forecast real estate phenomena such as future transaction levels
  • Extend insight capabilities through techniques such as NLP and deep learning
  • To work closely with the Data Engineering function on data preparation and ETL tasks
  • To be able to disseminate findings to a range of internal and external stakeholders
  • To be able to advise other parties on best practice regarding data analysis

Experience and Skills:
  • Strong and demonstrable knowledge on statistical methods
  • Machine Learning
  • Spatial Analytical methods
  • Proven experience in using quantitative methods for research
  • Knowledge of Real Estate industry and its economics beneficial
  • Ability to deal with senior members and stakeholders
  • Train and mentor colleagues on technical aspects
  • Strong communicator

If this sounds like the role for you then please apply today!

Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.

Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website:

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