Data Analyst Programmer

12-month Fixed Term Contract, with potential for extension.

SEBI-Livestock is a dynamic and innovative organisation tasked with improving data and evidence in low- and middle-income countries to support better informed decision making. We provide an extensive data driven monitoring and learning service to the Bill and Melinda Gates Foundation in tracking their livestock investments. In addition, we convene a large livestock data network, Livestock Data for Decisions (LD4D) to help achieve common goals.  

We are seeking a methodological, rigorous and service-oriented individual to support data processing in SEBI-L and provide data support services to deliver to the Bill and Melinda Gates Foundation.  The post-holder will write code that is scalable, tested and validated to process project data. 

The postholder will work on two project areas: 

• The validation of project outputs from SEBI-L machine learning literature review tool
• The building of scalable, tested and validated data pipeline to process livestock data. 

The opportunity

This role will play a crucial part in supporting the SEBI-L team in transforming and importing livestock data into the SEBI-L platform.

Responsibilities will include:

• The writing, running and maintenance of scripts to automate and test data processing workflows; 
• Ensuring code is version controlled, validated and robust in collaboration with other team members; 
• Supporting the automating and running of livestock models and analyses.

Within this role, there is an opportunity to develop data visualization skills and to work on projects in Machine Learning and Natural Language Processing. 

This position is based within SEBI-Livestock, the Centre for Supporting Evidence Based Interventions in Livestock,  which is hosted by the Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh. SEBI-Livestock offers a collaborative, fast-paced environment with opportunities for learning, growth and the chance to contribute to addressing real-world challenges. 

Your skills and attributes for success:

• Educated to degree level in a numerical discipline such as Bioinformatics, Computer Science, Mathematics or equivalent;
• Demonstrable experience of R programming  and modular code;
• Basic knowledge and experience of Python and SQL databases;
• Good knowledge and experience of data science technologies and of good software engineering practices including use of version control and implementation of unit and integration tests;
• An interest in exploring the application of new technologies including Natural Language Processing and Machine Learning

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