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Data Analyst
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University of Edinburgh
Edinburgh
161 days ago

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

Qualifications/Training

Essential

  • An honours degree in a scientific or numerate subject
  • PhD (or near completion) OR equivalent relevant experience.

Experience

Essential

  • 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)

Desirable

  • Understanding and/or experience of health records and health informatics
  • Experience in public engagement

Knowledge, Skills and Competencies

Essential

  • 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

Desirable

  • 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.)

9. Dimensions

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.

Salary
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.

Pension Scheme
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.

For further information please visit our pension’s website: http://www.ed.ac.uk/schools-departments/finance/pensions/scheme-details/uss

Right to Work

In accordance with the Immigration, Asylum and Nationality Act 2006 and Immigration Act 2016 the University of Edinburgh, as an employer, has a legal responsibility to prevent illegal working and therefore must check that all employees are entitled to work in the United Kingdom (UK).
To do so, the University requires to see original documents evidencing right to work in the UK before commencement of employment and this is normally carried out at interview. Details will be provided in any letter of invitation to interview.

For further information on right to work please visit our right to work webpage

If you are from outside the EEA and not currently eligible to work in the UK, there are visa routes that may be available to you, for example:

  • Tier 1 (Exceptional Talent): If you are an academic in the field of sciences; humanities; engineering; medicine; digital technology; or the arts, it may be possible for you to apply for a Tier 1 (Exceptional Talent) visa. This route requires you to apply to be endorsed as an internationally recognised leader or emerging leader in your particular field by a designated competent body (Arts Council England, British Academy, Royal Academy of Engineering, Royal Society, Tech City UK). However, if you are applying for a senior academic role, e.g. Professor/Reader there is an accelerated route to endorsement. Further information can be found on the UKVI website
  • Tier 2: The University is a UKVI licensed sponsor and is able to issue a Certificate of Sponsorship (CoS) to successful candidates who are offered highly skilled roles and meet the eligibility criteria. The CoS enables candidates to apply for a Tier 2 (general visa).
    Please note if you were last granted leave to stay in the UK in any Tier 2 category in the 12 months immediately preceding an application and the leave has
  • ended or expired.
  • the CoS which led to that grant of leave was issued for more than 3 months, and
  • you are either:
  • o applying for entry clearance from outside the UK, or
    o you are in the UK and had a previous period of Tier 2 leave, but then changed (‘switched’) into a different immigration category and now wishes to apply again under Tier 2.
    You must wait 12 months before applying again.

Further information about whether you require a visa and other visa routes can be found at: www.gov.uk/check-uk-visa

Application Procedure
All applicants should apply online by clicking the “apply” button at the foot of this page. The application process is quick and easy to follow, and you will receive email confirmation of safe receipt of your application. The online system allows you to submit a CV and other attachments.

Closing date: 22nd July 2020 at 5pm.

Interview date
You will be notified by email whether you have been shortlisted for interview or not.

The University reserves the right to vary the candidate information or make no appointment at all. Neither in part, nor in whole does this information form part of any contract between the University and any individual.




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


The College of Medicine and Veterinary Medicine
The College of Medicine and Veterinary Medicine The College of Medicine and Veterinary Medicine traces its origins back nearly 500 years (Darwin, Simpson and Conan-Doyle were students here) and is internationally renowned for its research and teaching. Professor Moira Whyte is the Head of College, the only conjoint Medical and Veterinary Medical School in the UK. The College employs over 3000 academic and support staff. The College has two Schools, the Edinburgh Medical School comprising 3 Deaneries; Biomedical Sciences; Molecular Genetic and Population Health Sciences and Clinical Sciences and the Royal (Dick) School of Veterinary Studies.

The Royal (Dick) School of Veterinary Studies

Edinburgh Medical School: Biomedical Sciences

Edinburgh Medical School: Biomedical Sciences, Biomedical Teaching Organisation

Edinburgh Medical School: Molecular, Genetic and Population Health Sciences

Edinburgh Medical School: Clinical Sciences

The undergraduate medicine teaching programme in the College enjoys a high reputation nationally and internationally, with over 1,300 students enrolled on the MBChB and Intercalated courses and nearly 1000 on the Veterinary Sciences BVS and related programmes. In addition, approximately 2000 students are currently enrolled in the College’s taught and research post-graduate courses, including an extensive range of online distance learning diplomas and degrees. They are trained by over 1000 outstanding academic staff. Details of PhDs, research programmes and studentships are available through our interdisciplinary research institutes and centres.

The academic disciplines within Medicine are largely concentrated in the two teaching hospital campuses, the Royal Infirmary at Little France and the Western General Hospital. Both have extensive new infrastructure with major research institutes and state of the art research facilities on clinical sites. Edinburgh hosts a number of prestigious MRC and BHF Research Centres. The approach is interdisciplinary, with basic and clinical researchers working together at the laboratory bench and in our clinical research facilities to address major themes in basic, clinical and translational medicine.

The Royal (Dick) School of Veterinary Studies on the Easter Bush Campus houses outstanding teaching and clinical facilities as well as the splendid Roslin Institute, one of the world’s leading veterinary research centres. The College offers outstanding opportunities to address ‘One Health’ and Global Health problems of the highest international priority.

Research Excellence Framework (REF) 2014

The College’s reputation as one of the world’s leading centres of medical and veterinary medical research has been reaffirmed by its UK REF2014 results. Medicine, the University’s largest submission, was ranked in the top 5 in the UK. Veterinary Medicine came 1st in the UK, and retained its position as the UK’s top Vet School. It made a joint submission with Scotland’s Rural College (SRUC). Neuroscience was ranked 3rd in the UK out of 82 submissions, representing a major advance. Overall, 84% of the College’s research activity was rated world leading or internationally excellent (3* and 4*). In terms of 'one medicine' research (human and animal medicine), the University of Edinburgh's research power (quality x volume) is the strongest in the UK.

The University of Edinburgh
For more than four centuries, our people and their achievements have rewritten history time and again. They’ve explored space, revolutionised surgery, published era-defining books, paved the way for life-saving medical breakthroughs and introduced to the world many inventions, discoveries and ideas from penicillin to Dolly the sheep. We have believed that anything is possible, we still do.
The latest Research Excellence Framework highlighted our place at the forefront of international research. This adds to our international reputation for the quality of our teaching and our student experience excellence. The University is proud of its success with online teaching initiatives, with 2550 students currently studying its online distance learning postgraduate programmes, and a total to date of more than 2 million enrolments for Edinburgh MOOCs.

As a member of staff, you will be part of one of the world's leading universities, with 20 Schools spread over 3 Colleges that offer more than 1600 undergraduate and 600 postgraduate programmes to over 41,000 students each year. Professional services are critical to this success as well as our world-class teaching, research and student facilities. In fact, we are one of the top employers in Edinburgh, with over 14,500 people spread across a wide range of academic and supporting roles.

As a world-changing, world-leading university, we offer an exciting, positive, creative, challenging and rewarding place to work. We give you support, nurture your talent, develop and reward success and integrate academic, professional and personal career goals, as well as give your career the benefit of a great and distinguished reputation. In addition, our employees benefit from a competitive reward package and a wide range of staff benefits, which include generous holiday entitlement, a defined benefits pension scheme, staff discounts and much more. Access our staff benefits page for further information and use our reward calculator to find out the total value of pay and benefits provided.

The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality. The University has a range of initiatives to support a family friendly working environment, including flexible working and childcare vouchers. See our University Initiatives website for further information.

University Family Friendly Initiatives

Equality Networks:

Staff Pride Network for LGBT+ colleagues and allies
Disabled Staff Network

The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

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