View Vacancy -- Scientific Data Analyst - MLC 2436

Open Date27/06/2024, 10:30 /*generated inline style */Close Date/*generated inline style */ 21/07/2024, 23:55 /*generated inline style */ Research Institute MRC Mary Lyon Centre /*generated inline style */ Research Institute / Unit Information The (MLC) is located in an expanding science and innovation campus in Oxfordshire and is an internationally renowned centre at the forefront of genetics research. As the hub of the new National Mouse Genetics Network, the specialist facilities and capabilities of the MLC support a number of research groups across the UK to accelerate our understanding of human diseases, such as cancer, developmental disorders and neurodegeneration. /*generated inline style */ UK Research and Innovation is a new entity that brings together nine partners to create an independent organisation with a strong voice for research and innovation, more information can be found at

/*generated inline style */ Band MRC - 4 /*generated inline style */ Location Harwell Campus, Oxfordshire /*generated inline style */ Salary £39,375 - £41,843 per annum, dependent on skills and experience /*generated inline style */ Contract Type Fixed Term /*generated inline style */ Job Type Technical & Scientific Professionals /*generated inline style */ Full Time / Part Time Full Time /*generated inline style */ Contract Length Thirty months /*generated inline style */ Job Description

Overall Purpose:

We are seeking a scientific data analyst to join the data management team at the Mary Lyon Centre at MRC Harwell (MLC). This is an opportunity to use knowledge of in-vivo biological data to build skills in data management. 

The Mary Lyon Centre runs and develops specialised screening tests to investigate mouse gene function and develop preclinical models for human genetic disorders. These tests cover behavioural, physiological and metabolic assays. These generate complex datasets that present unique challenges to data management and analysis. The data management department works to validate data prior to its release to researchers and collaborators. This work will involve maintaining and developing validation pipelines, managing data and communicating about data quality across projects, and improving our capacity to validate scientific datasets. 

This role would suit a recent PhD graduate in life-sciences interested in applying their knowledge of in-vivo or other datasets and developing skills in data management and data validation. For example, a PhD graduate with experience in behavioural or metabolic assays and relevant datasets, who has a desire to translate this knowledge into software solutions and to learn programming skills.

Main Duties/Key Responsibilities:

Use existing data management pipelines to conduct comprehensive data validation of numerous complex scientific datasets Learn skills to develop and maintain data analysis pipelines for varied biological datasets (Python, SQL, database management) Use knowledge of in-vivo measurements and liaise with animal technicians and researchers to determine necessary steps in data validation Flag, review, investigate and resolve issues in in-vivo datasets Manage and maintain database tables and relationships within database Work day-to-day within the data management team, discussing current technical issues and informing key stakeholders on plans and solutions Communicate effectively to the data management team and stakeholders when discussing and presenting data, data issues and processes Structure communication with technical and non-technical teams to diagnose data issues and ensure information is logged systematically Support and mentor junior team members Collaborate with software developers to standardise and automate data upload and validation Ensure that data is validated according to schedule, prioritising work to ensure that schedules are maintained Contribute to data standards, documentation, protocols and to Gitlab repositories Expand knowledge of in-vivo measurements as MLC innovates and integrates new datasets, such as those for telemetry and video-tracking

Working Relationships:

You will be part of the Data Management team and will report to the Head of Data Management. The Data Management team works closely with the phenotyping team as they gather datasets. The Data Management team will also work alongside other informatics teams.

Additional Information:

Hybrid working is possible with this role.

We are reviewing applications on a rolling basis and reserve the right to close the advert early.

/*generated inline style */ Person Specification

Education/Qualifications/Training Required:

Essential:

 Qualification in the life sciences (PhD or MSC) or strong equivalent experience 

Desirable:

 Project management training or qualifications Training or qualification in relevant technical skill such as coding or database management

Previous Work Experience Required:

Essential: 

Experience of managing, validating and analysing scientific datasets Demonstration of consistency and independence when working on long-term projects Experience of making decisions and communicating to teams and stakeholders 

Desirable:

Evidence of working independently on a technical project Experience in building and using technical pipelines for data management

Knowledge and Experience:

Essential: 

Advanced understanding of in-vivo experimentation Evidence of technical skill and aptitude in at least one of the following: code, SQL, database management, Excel VBAs, Tableau/Power BI or others if justified Ability to grasp complexity of scientific datasets

Desirable:

Knowledge of concepts in data management and data analysis Understanding of data repository architecture and relational database management Experience of statistics such as power calculations and linear mixed-effect models

Personal skills/Behaviours/Qualities:

Essential:

Possess strong communication skills Be proactive and self-organised Capable of working under pressure to meet deadlines Able to develop and maintain effective professional working relationships Willing to learn new technical skills as project goals change

/*generated inline style */