The Usher Institute is seeking an experienced Data Analyst within the Centre for Medical Informatics working with the newly formed Consortium for the Study of Pregnancy Treatments (Co_OPT) to develop methods for the large-scale study of medicines in pregnancy. The post holder will be working with large amounts of highly complex confidential electronic health data from multiple sources including electronic health records, population registries and clinical studies (from the UK, Europe and North America) and providing analytical expertise to the Co_OPT team, which includes epidemiologists, clinicians and statisticians.
The successful candidate should have an honours degree in a scientific or numerate subject, PhD (or near completion), with a good postgraduate experience working in data analysis and writing complex queries to interrogate databases (e.g. Ms SQL, MySQL, PostgreSQL and Oracle). The work demands close attention to detail and the experience to prioritise, identify and achieve deadlines and use good judgement and initiative. The ability to use mainstream data science programming languages (such as Java, Python) for data extraction, transferring and transforming data, and statistical data analysis with experience in using one or more statistical software packages (e.g. R, SAS, STATA or similar) is essential. Good archiving, data management, and organizational skills along with the ability to work well within a multi-disciplinary team are also crucial to the post.
The post is available from November 2020, full-time (35 hours) although a part time (28 hours per week) or flexible working pattern may be possible, and is fixed-term for 12 months initially.
Please include your CV and a supporting statement with details of how you meet the knowledge, skills and experience required for this post.
Informal enquiries may be directed to Dr Sarah Stock (Sarah.Stock@ed.ac.uk).
1. Job Details
Job title: Data Analyst
Deanery/Support Department: Molecular, Genetic & Population Health Sciences / Usher Institute
Unit: Centre for Medical Informatics
Line manager: Dr Sarah Stock
2. Job Purpose
The post holder will be working with the newly formed Consortium for the Study of Pregnancy Treatments (Co_OPT) to develop methods for the large-scale study of medicines in pregnancy. The post holder will be working with large amounts of highly complex confidential electronic health data from multiple sources including electronic health records, population registries and clinical studies; from the UK, Europe and North America. The post holder will provide analytical expertise to the Co_OPT team, which includes epidemiologists, clinicians and statisticians. The post holder will identify gaps in information, conduct analyses to interrogate and resolve issues and challenges with these real world datasets (e.g., coding errors, missing, incomplete and/or inconsistent data), and assist with development of algorithms to identify medicine use, indication for treatment and clinical outcomes, combining information from different data sources. The post holder will also help apply for access and approvals for data use, and be responsible for developing, processing, maintaining and documenting the datasets, analytic approaches and algorithms, and contribute to the statistical analysis.
3. Main Responsibilities
Writing complex queries to investigate medicine use in pregnancy and healthcare outcomes of mothers and babies using programming languages and database query languages to interrogate complex datasets containing health data from multiple sources (including population registries, clinical trials and electronic health records). Approx. 15% of time
Creating new datasets by extracting data on medicine used in pregnancy from unstructured and structured entries in electronic healthcare records. Approx. 15% of time
Producing a range of different types of descriptive analyses of these complex data for epidemiologists, clinicians and statisticians contributing to the academic activities of team. Approx. 15% of time
Assisting with project management including data access applications, liaising with data holders and ensuring governance requirements are met for data use and reuse. Approx. 15% of time
Exploring and advising on the most appropriate IT and data management tools and methods for data extraction and handling these complex datasets. Approx. 10% of time
Checking and processing data, documenting and maintaining well-structured records of all changes to datasets and data queries. Approx. 10% of time
Assisting with the analysis of data and providing statistical analysis support to the Co_OPT team. Approx. 10% of time
Reviewing relevant literature around various pregnancy outcomes in conjunction with different health-related coding systems. Approx. 10% of time
4. Planning and Organising
The post holder will:
- Plan, develop and determine own work priorities in order to meet timelines for multiple responsibilities for work for Co_OPT.
- Identify new relevant data sources, manage applications for data access and ensure governance requirements are met.
- Identify gaps in analysis plans for complex data and then find and present solutions for these gaps.
- Plan time and prioritise tasks effectively to maintain and provide data for different members of the team working to different deadlines.
- Facilitate collaboration and data sharing as required with other research groups.
- Conduct statistical analyses of health data from a variety of sources.
- Prepare and present results in oral and written reports and publications.
5. Problem Solving
The post holder will:
- Develop analytic approaches to complex health-related data to underpin complex algorithm development (e.g.: defining exposures and health related outcomes in the face of missing, incomplete or inconsistent data; developing algorithms for exposures and births at different gestational ages, varying time between treatment and delivery, different formulations and dosages of drugs and presence of co-morbidities).
- Resolve complex data analysis challenges, discussing as required with epidemiologists, statisticians and clinicians in the team.
6. Decision Making
The post holder will determine most appropriate tools and approaches for querying, analysing, maintaining and documenting complex health-related data.
7. Key Contacts/Relationships
- Internal: Dr Sarah Stock (line manager), lead for Co-OPT; Co_OPT data administrator; eDRIS and NHS eHealth teams; other researchers and fellows at the Centre for Medical Informatics
- External: Other Co_OPT collaborators in UK, Europe, North America and Australia.
8. Knowledge, Skills and Experience Needed for the Job
- An honours degree in a scientific or numerate subject
- PhD (or near completion) OR equivalent relevant experience.
- At least two years postgraduate experience working in data analysis
- Experience in writing complex queries to interrogate databases (e.g. Ms SQL, MySQL, PostgreSQL and Oracle)
- The ability to use mainstream data science programming languages (such as Java, Python) for data extraction, transferring and transforming data, and statistical data analysis
- Experience in using one or more statistical software packages (e.g. SAS, STATA, R or similar)
- Understanding and/or experience of health records and health informatics
- Experience in public engagement
Knowledge, Skills and Competencies
- Good archiving, data management, and organizational skills
- Ability to work well within a multi-disciplinary team
- Excellent written and oral English language communication skills
- Naturally inclined towards careful attention to accuracy and detail
- Understanding of the principles of security and confidentiality of personal data in a research context
- Ability to write clear and concise documentation
- Ability to work independently, as well as to judge appropriately when to seek advice and support from other members of the team
- Experience in authoring peer-reviewed manuscripts
- Knowledge of medical ontologies/vocabularies and health record coding systems (e.g., ICD, Read and SNOMED codes)
- Knowledge and/or experience of natural language processing and its application on medical records
- Understanding and/or experience of the application of statistical methods to epidemiological studies
- Understanding and/or experience of machine learning or data mining models (e.g., clustering, support vector machines, Bayesian networks or artificial neural networks etc.)
Co_OPT is led by Dr Sarah Stock, funded as part of a Wellcome Trust Clinical Research Career Development Fellowship. The post holder will be based in the Centre for Medical Informatics in the Usher Institute of Population Health Sciences, University of Edinburgh. The group’s main base is Nine BioQuarter at Little France. Dr Stock is also a member of the Tommy’s Centre for Maternal and Fetal Health and affiliated to the MRC Centre for Reproductive Health. She interacts closely with research groups there and in other centres in Edinburgh, including the Centre for Inflammation Research, Centre for Cardiovascular Science and Edinburgh Clinical Trials Unit.
- This post is 1.0 FTE, and funded for 2 years in the first instance, starting as soon as possible.
- The post-holder will be expected to work flexibly to fit the requirements of the project.
- The post-holder should be willing to undertake travel both within the UK and outwith the UK when required for scientific and collaborator meetings
10. Job Context and any other relevant information
Co_OPT is a new collaborative cross-disciplinary consortium for the study of pregnancy treatments. The initial focus of Co_OPT will be on antenatal corticosteroid treatment. With consortium members contributing data from thirteen datasets (3 million women and their children) Co_OPT will comprehensively describe how antenatal corticosteroid treatment is used across a variety of settings; determine the short and long-term outcomes of antenatal corticosteroid treatment and determine characteristics that influence maternal and infant outcomes to develop predictive models for their use.
The role is grade UE07 and attracts an annual salary of £33,797 to £40,322 for 35 hours each week. Salary is paid monthly by direct transfer to your Bank or Building Society account, normally on the 28th of the month. Salaries for part-time staff are calculated on the full-time scales, pro-rata to the Standard Working Week.
This post is available on a fixed term basis, with a working pattern of 35 hours per week for 12 months.
This role is grade UE07 and therefore the post holder is automatically included in membership of the Universities Superannuation Scheme (USS), subject to the USS membership criteria, unless they indicate that they choose not to join the Scheme.
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Deanery of Molecular, Genetic and Population Health Sciences
Molecular, Genetic and Population Health Sciences is one of three Deaneries in Edinburgh Medical School which, together with the Royal (Dick) School of Veterinary Studies, makes up the College of Medicine and Veterinary Medicine. The Deanery is headed by Professor Sarah Cunningham-Burley and comprises the Institute of Genetics and Molecular Medicine (IGMM), the Usher Institute of Population Health Sciences and Informatics, the Division of Pathology and the Edinburgh Clinical Trials Unit. The Deanery currently attracts annual research grants of around £40M, including a number of full programme grants, and has around 630 employees including 39 Professors, over 260 other academic members of staff and 330 members of support staff. The Deanery operates across three University of Edinburgh sites; the Western General Hospital campus, the Central Area, and Little France. Staff contribute undergraduate and postgraduate teaching and offer on-campus and on-line programmes. There is a vibrant PhD community in both IGMM and the Usher Institute.
Molecular, Genetic and Population Health Sciences
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