Data Scientist (Genomic Surveillance)

The Opportunity We are looking for Data Scientists to join the MalariaGEN Data Analysis and Interpretation Team in our Genomic Surveillance endeavour. The Project and the Organisation We need effective ways of combating current and future drug and insecticide resistance that will emerge as new malaria control tools are deployed. Genetic data are routinely used in managing viral and bacterial epidemics, and similar approaches are needed to target malaria control interventions for maximum impact and sustainability. The Malaria Genomic Epidemiology Network was founded in 2005 and has grown to become a data-sharing network with partners in over 40 countries. Our goal is to support and accelerate the use of genomic surveillance data by malaria control programs and policymakers to make effective informed decisions. As part of the national response, our team is also playing a pivotal role in the Genomic Surveillance of COVID-19, tracking and analysing the spatiotemporal spread of this disease to directly influence and guide policy makers to control the pandemic. Our Team and the Role We are a dynamic, diverse, and energetic team of dedicated data scientists with a profound understanding of and passion for biology and epidemiology of infectious disease. We analyse genomic data using cutting-edge methodologies - often developed in-house, interpret the results, and distil them into actionable insights for health organisations. As a result of investments from the Bill and Melinda Gates Foundation as well as other funders, and after a successful campaign last year, we are continuing to recruit exceptional data scientists to further support our leading genomic surveillance work. You will contribute to supporting and influencing local and global health organisations in their surveillance activities to achieve well-informed, impactful and sustainable interventions. You will also lead the production of analysis that answer specific, relevant and crucial questions that build upon decades worth of research, as well as the production of open data resource publications to maintain MalariaGEN’s status as a world leader in malaria genomic surveillance. About you We are looking for data scientists at the beginning of their career who are keen to work at the cutting edge of genomic research and translation and are eager to develop their analytical skills as part of a dynamic and welcoming team. We are open to consider a broad range of background skills and experience, with successful candidates having an aptitude in more than one of the following areas: Undergraduate qualification in computational biology, population genetics, epidemiology or statistics; or undergraduate qualification plus relevant experience in quantitative analysis. Base computer programming skills for advanced statistical analysis and large-scale data management Demonstrable knowledge of statistical methodologies Due to the multidisciplinary nature of the questions tackled, the willingness to effectively integrate with a diverse team of peers and engage positively in scientific discussions is a strong requirement. Essential Skills Technical Skills: Undergraduate qualification or relevant experience in computational biology, population genetics, epidemiology, statistics, or other relevant area of quantitative analysis Proficient computer programming skills preferably for the analysis of large scale data Ability to rapidly gain practical knowledge in new operational environments Ability to successfully contribute to complex analytical projects involving multiple partners Ability to deliver high-quality analytical outputs Knowledge of statistical methodologies Competencies and Behaviours Eager to learn new skills Enthusiastic, flexible and proactive Proven ability to work independently Ability to communicate effectively about complex technical matters with both technical experts and non-specialists Effective written and oral communication and proven ability to work in a collaborative environment Ability to work effectively with colleagues leading other areas of work within a team environment Ideal Skills Technical Skills: Experience of working in scientific environments Understanding of and experience with software engineering best practices Deep understanding infectious diseases biology and epidemiology Knowledge and experience in population genetics Successful in producing scientific outputs Familiarity with genomic and bioinformatics tools and methods Large-scale computing using on premise and cloud based HPC facilities Experience with the use of machine learning to answer scientific questions
Date and time
Application Deadline: 
Thursday, April 22, 2021 - 12:00