Full Time, Part Time, Flexible, Permanent
About the Role
We are currently seeking an experienced and motivated Data Analyst to join our dynamic team within a global research organisation. This is an exciting opportunity for a data professional with a strong background in analytics and database management to play a key role in the development and delivery of high-impact health research projects.
As a Data Analyst, you will support the Data Analytics Manager in leading data-focused projects across the organisation and its partner networks. You will contribute to the development and optimisation of database systems, deliver detailed analyses for research studies, and help guide data governance and quality practices.
The role can be based in our Cambridge (Oakington) or Norwich office. We offer hybrid working as standard, which is Monday, Wednesday and Friday in the office and Tuesday and Thursday working from home. This role offers flexible working within the usual office hours of Monday – Friday, 9am – 5pm. Part time and close to full time working arrangements are available.
Primary responsibilities
- 1) Solve complex problems in study and healthcare data, transforming large and diverse datasets into actionable insights that drive evidence-based decisions and improve patient outcomes.
- 2) Design, construct, install, test and maintain data collection and management systems
- 3) Assist in the development of the data analytics function and team, continuously striving to optimise data utilisation and delivery
- 4) Provide support and guidance to the team in the integration of data management technologies and software engineering tools for custom data collection applications
- 5) Employ a variety of languages and tools (e.g. scripting languages) to combine systems together ensuring seamless integration of data across multiple databases SQL, queries
- 6) Building APIs for data consumption; Integrating external or new datasets into existing data pipelines
- 7) Continuously monitor and test the system to ensure optimized performance, coaching key stakeholders in new ways of working
- 8) Build, maintain and oversee data collection platforms for specific organisational projects
- 9) Set up automated integration processes for Patient Reported Outcomes into various data collection platforms
- 10) EMR/EDC integration with Registry Database
QUALIFICATIONS AND CERTIFICATIONS
Bachelor’s degree in computer science, Engineering, Maths or equivalent qualification
EXPERIENCE AND SKILLS
- 1) Strong working knowledge of SQL/T-SQL (Essential)
- 2) At least three years’ experience of working with large databases.
- 3) Experience of developing and maintaining data dictionaries for databases Knowledge of statistical analysis tools (e.g. R, STATA, SPSS, SAS)
- 4) The ability to effectively communicate to key project stakeholders including Senior Management
- 5) The ability to coach, mentor and support junior team members and provide training and guidance as necessary
- 6) Strong project management skills, the ability to work autonomously and prioritise own activities appropriately
- 1) Experience with REDCap EDC development, including designing electronic case report forms, managing study workflows, and ensuring data quality in clinical trials.
- 2) Experience working with modern data architectures and cloud platforms such as Microsoft Azure, Google Cloud Platform (GCP) or Snowflake
- 3) Knowledge of epidemiology, public health and clinical research
About Optimum Patient Care
Optimum Patient Care has been supporting chronic disease management and research in primary care for over 15 years. We are a not-for-profit social enterprise which provides a range of services to over 1000 GP surgeries across England, Scotland, Wales and Northern Ireland. Our services include clinical audit and review services, IG-compliant data extraction services, and research support services. Our services are provided at no cost to participating practices and freely available to all GP surgeries across the UK. Our anonymised research database, OPC Research Database (OPCRD), is one of the largest electronic health record databases in the world for research use, with over 17 million anonymised patients.
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