Data Analyst

Data Analyst

The International Center for Tropical Agriculture (www.ciat.cgiar.org) develops technologies, innovative methods and research-based solutions in agriculture and the environment, in order to increase prosperity and improve human nutrition for a sustainable food future. CIAT conducts research for development primarily in tropical regions of Latin America, Africa, and Asia. CIAT is a member of the CGIAR Consortium (www.cgiar.org), a global research partnership for a food secure future.

About the Position

The CIAT Asia regional office in Hanoi is recruiting a Data Analyst to support research projects using household, markets and agronomic survey data to generate novel insights in opportunities and constraints facing smallholder farming households and the women, men and children dependent on rural livelihoods. The Data Analyst will work within CIAT research teams such as Climate Resilient Agriculture and Agroecosystems and Sustainable Landscapes to provide data cleaning, pre-processing and analysis on socio-economic, value chain and biophysical aspects of sustainable production in Southeast Asia.

A recent BSc graduate with aspirations to rapidly acquire experience and skills and expand their professional horizons will thrive in this position. The position is available for nationals of Viet Nam.

Responsibilities

• Collect, organize and carry out basic data cleaning procedures such as documenting missing values, data inconsistencies and finding extreme values (outliers) to facilitate consistent and harmonized datasets.
• Compute a range of descriptive statistics. Basic programming for various segmentation, regression analysis and other mixed models of analysis.
• Support the creation of reports, communication material based on the data analysis and present to stakeholders whenever required.
• Conduct literature review to contextualize and critically assess relevance of the data analysis and interpretation for a specific purpose.
• Visualize data in easy-to-understand charts and graphs in order to interpret trends, patterns and correlations.
• Document and archive data into digital repositories.
• Contribute to data management policies and procedures.

Requirements

• BSc in a quantitative program such as Economics, Statistics, Computer Science or related fields
• Possess a working knowledge in a range of statistical and segmentation techniques
• Strong desire to learn, advance in applied sciences and acquire new skills is required. Humility and curiosity to ask questions is essential.
• Experience with statistical packages, preferably Stata or R, to assess survey data
• Competency in Microsoft Office Suite, i.e. Word, Excel and PowerPoint
• Good English communication skills (speaking, reading and writing) is required
• Self-motivated, detail-oriented and organized critical thinker with an ability to handle multiple priorities, manage assignments independently, and work under tight deadlines.
• Demonstrated capacity to work independently and as part of interdisciplinary teams in a culturally diverse and inclusive work environment

Terms of employment

The position is full-time, limited to applicants of Vietnamese nationality. Contracts are issued and renewed annually, based on performance. This position will be subject to an initial three-month probation period. CIAT is an equal opportunity employer and strives for staff diversity.

Applications

To be considered for this position, please send an email to [email protected] with the subject line “Data Analyst”. In your email, please include:

1. A cover letter illustrating your motivation to apply and suitability for the above position against the listed qualifications and work responsibilities, and;
2. A detailed curriculum vitae, including the name and email addresses of one professional referee who has worked either as your professional or academic supervisor and is knowledgeable about your skills and professional abilities.

The closing date for applications is 10th of June. We will close the advert earlier when a suitable candidate has already been identified.