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Data Scientist


Summary Sheet: I.T. & Communications

    
Advertiser NameCarnall FarrarAdvertiser Type:Company
Classification:I.T. & CommunicationsSubclassification:
Country:United KingdomLocation:United Kingdom
Language:English - United Kingdom (en-GB) Contact Name:>Carnall Farrar
Employment Type:PermanentWorkhours:Full Time



Position: Data Scientist


Description:

Job Overview
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 statistical techniques 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.

Overarching Profile
•Minimum Bachelor's degree in relevant area; advanced degree in relevant area would be advantageous
•Passion for the potential of data and analytics to help build the team and evangelise across Carnall Farrar
•Excellent analytical problem-solving skills and experience building predictive models
•Proficiency using relational database systems and SQL and in statistical/machine learning tools (e.g. Python, R)
•Experience in data scraping/mining and analysing unstructured data is advantageous
•Excellent written and verbal communication skills to work collaboratively with others in the organisation
•Commitment to giving and receiving constructive feedback and coaching to support development
•Strong drive and resilience

Responsibilities
•Work with clients to bring analytical insights to address their toughest problems
•Use analytical tools to gather and analyse data, understand relationships between metrics, identify insights, communicate them clearly, and develop predictive models
•Identify and assess data sources which could add value to products and client projects
•Create and structure data warehouses; and extract, transform and load data
•Work with leadership to identify key new product initiatives to drive growth
•Collaborate with consulting teams to identify and execute on opportunities to build data science products and models
•Develop processes and tools to measure the quality and and effectiveness of data sources, products and models over time and improve upon them





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