Position Overview & Specifications
An exciting opportunity has arisen for a pro-active and enthusiastic full-time Data Analyst to join a team of health economists, collaborating with statisticians, epidemiologists and clinicians working on developing and applying innovative scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured healthcare data. You will be based within the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS) at the Botnar Research Centre, Oxford.
As Data Analyst you will extract, clean, validate, investigate, prepare, and report health-related data using the R programming software and craft efficient and re-usable software solutions to novel problems in the form of R libraries and programming pipelines for use within the team and with collaborators. You will provide written input into the development of health economics analysis plans and function as a source of information and advice to other members of the group on statistical methodologies and procedures. You will also assist team members in their own development of R scripts and help identify more efficient ways to achieve desired outputs.
You will hold, or be close to completion of, a post graduate qualification or equivalent experience in Statistics, Epidemiology, or numerate/problem solving subjects and programming experience giving the ability to write structured, documented, and reusable code to analyze data in R . You will also be proficient in in publishing reproducible code and in the use of version control systems (e.g., Git/GitHub) and have strong quantitative and analytical skills with substantial knowledge of good data management principles and workflow in the context of health research. A Master’s degree in any of the following fields: Mathematics, Statistics, Statistical Science, Statistical Data Analytics, Medical Statistics, Data Science, Epidemiology, or equivalent and formal training in R Programming, Machine Learning, Data Analytics, Statistics, or Applied Mathematics would be desirable.
This is a full-time fixed-term appointment for 18 months. Part-time being available/considered.
The closing date for this position is 12 noon on 19 April 2023, Interviews are planned for the 9th and/or 11th May 2023 . You will be required to upload a supporting statement and CV as part of your online application.
As Data Analyst you will extract, clean, validate, investigate, prepare, and report health-related data using the R programming software and craft efficient and re-usable software solutions to novel problems in the form of R libraries and programming pipelines for use within the team and with collaborators. You will provide written input into the development of health economics analysis plans and function as a source of information and advice to other members of the group on statistical methodologies and procedures. You will also assist team members in their own development of R scripts and help identify more efficient ways to achieve desired outputs.
You will hold, or be close to completion of, a post graduate qualification or equivalent experience in Statistics, Epidemiology, or numerate/problem solving subjects and programming experience giving the ability to write structured, documented, and reusable code to analyze data in R . You will also be proficient in in publishing reproducible code and in the use of version control systems (e.g., Git/GitHub) and have strong quantitative and analytical skills with substantial knowledge of good data management principles and workflow in the context of health research. A Master’s degree in any of the following fields: Mathematics, Statistics, Statistical Science, Statistical Data Analytics, Medical Statistics, Data Science, Epidemiology, or equivalent and formal training in R Programming, Machine Learning, Data Analytics, Statistics, or Applied Mathematics would be desirable.
This is a full-time fixed-term appointment for 18 months. Part-time being available/considered.
The closing date for this position is 12 noon on 19 April 2023, Interviews are planned for the 9th and/or 11th May 2023 . You will be required to upload a supporting statement and CV as part of your online application.