We are looking for a Data Scientist who will support our emerging Health Analytics business with insights gained from aggregating and analysing healthcare data. The ideal candidate is adept at developing products that the broader consulting business can then deploy. They must have strong experience using a variety of data analysis methods, using a variety of data tools, building and implementing models, using standard statistical algorithms and creating/running simulations. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. 

Why choose Carnall Farrar?

When you join Carnall Farrar you will be working closely with our industry-leading partners and consultants, putting you in a great position to accelerate your path to becoming an accomplished business professional.

We offer on the job learning as well as access to an extensive range of in-house and external training opportunities.

The role 

This is an exciting new role for Carnall Farrar which we are anticipating the right candidate will shape and develop as they settle in. We do however expect the key responsibilities for this role to be:

  • Work with leadership to identify key new product initiatives to drive growth
  • Collaborate with consulting teams to identify opportunities to build data science products
  • Lead predictive modelling projects which aim to outperform incumbent models 
  • Create new data warehouses
  • Load data into a data warehouse and cleanse
  • Mine and analyse data from databases to drive optimisation and improvement of product development
  • Use statistics tools to analyse data to understand and model the relationship between different metrics and identity key insights
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques
  • Develop custom data models and algorithms to apply to data sets
  • Coordinate with different consulting teams to implement models and monitor outcomes
  • Develop processes and tools to monitor and analyse model performance and data accuracy
  • Contribute to development of current data pipelines 
  • Lead external data gathering and preparation exercises and assess the impact of new external data


  • A relevant Master's degree (a PhD would be advantageous) 
  • Significant experience manipulating data sets and building statistical models (in a business or academic environment)
  • Strong problem solving skills with an emphasis on product development.
  • Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
  • Strong experience in statistics, machine learning models and mathematical theory
  • Experience visualising/presenting data for stakeholders using amongst other software, Tableau
  • Experience working with and creating data architectures
  • Strong knowledge of SQL essential, plus comfort with either R or Python
  • Experience with a big data platform desirable e.g. Hadoop
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
  • Knowledge and experience in statistical techniques: GLM/Regression, Boosting, Trees, etc.
  • Knowledge and experience text mining and social network analysis preferred
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
  • Strong passion for learning new technologies fast
  • A drive to learn and master new technologies and techniques
  • Interest in healthcare is essential, but an in-depth knowledge of the NHS is not required

Application process

Please apply to recruitment@carnallfarrar.com with an up to date CV outlining, education / qualifications and awards; work experience; current remuneration details and contact details. You also need to supply a separate supporting statement explaining why you would like to be considered for the role. Applicants who fail to do so will not be considered for the post. All applications need to be submitted by 27 July 2018.

 Apply now