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Data Analyst II

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American Institutes for Research

UNAVAILABLE Remote UNAVAILABLE UNAVAILABLE US

Posted 11 days ago


Job Description:

Overview

AIR is currently seeking a Data Analyst II to join AIR's FEWS NET (The Famine Early Warning Systems Network) USAID funded project. The Famine Early Warning Systems Network (FEWS NET) is a leading provider of early warning and analysis on acute food insecurity around the world. Created in 1985 by the United States Agency for International Development (USAID) in response to devastating famines in East and West Africa, FEWS NET provides unbiased, evidence-based analysis to governments and relief agencies who plan for and respond to humanitarian crises. FEWS NET analyses support resilience and development programming as well. FEWS NET analysts and specialists work with scientists, government ministries, international agencies, and NGOs to track and publicly report on conditions in the world’s most food-insecure countries.

Ethiopians and Kenyans are encouraged to apply. Candidates hired for the position might initially start working remotely but will eventually have the option to work from one of our offices located in Addis Ababa, Ethiopia or Nairobi, Kenya, or continue to work remotely based in Ethiopia or Kenya.

About AIR:

Established in 1946, with headquarters in Arlington, Virginia, AIR is a nonpartisan, not-for-profit institution that conducts behavioral and social science research and delivers technical assistance to solve some of the most urgent challenges in the U.S. and around the world. We advance evidence in the areas of education, health, the workforce, human services, and international development to create a better, more equitable world.

AIR’s commitment to diversity goes beyond legal compliance to its full integration in our strategy, operations, and work environment. At AIR, we define diversity broadly, considering everyone’s unique life and community experiences. We believe that embracing diverse perspectives, abilities/disabilities, racial/ethnic and cultural backgrounds, styles, ages, genders, gender identities and expressions, education backgrounds, and life stories drives innovation and employee engagement. Learn more about AIR's Diversity, Equity, and Inclusion Strategy and hear from our staff by clicking here.

Responsibilities

The responsibilities for the position include:

The Data Analyst II will work with FEWS NET field offices and home office subject matter experts to define and manage data streams into the FEWS NET Data Warehouse to ensure the highest possible standards of quality and efficiency.

Write code using Python and Pandas to review historical data records for errors, gaps and outliers, define strategies to address those problems and implement those strategies to ensure the quality of historical data.

Produce data quality reports for USAID identifying gaps and errors that require additional data collection to be resolved.

Write data pipelines using Python, Pandas and Luigi to support automated ingestion of new data from remote sources via API links. Ensure that the data acquired is properly formatted to comply with system standards and review it for data quality.

Write data pipelines in Python, Pandas and Luigi to support data ingestion from client and partners by identifying outliers, evaluating data quality, cleaning and correcting data.

Develop clear data quality standards and protocols to disseminate to field offices and home office staff to improve data quality and upload efficiency.

Monitor the quality and efficiency of data uploads, write code that automates reporting on upload results, identify issues and constraints to high quality and efficient data uploads, and develop tools and training materials to build better data management capacity of staff.

Provide support and advice to client and partners in preparing and submitting new data.

Review and evaluate new data sets considered for inclusion in the data warehouse system and support the design of data templates, data standardization protocols, and the application of metadata standards.

Help implement analytical methodologies as user-facing tools using data pipelines

The Data Analyst will work to systematize data quality assessment and verification, assess data producing systems, and develop strategies to improve both.

They will oversee the review of each indicator against quality standards and complete a DQA checklist for each indicator.

They will also be responsible for capacity building of FEWS NET global staff and support Routine Data Quality Assessment (RDQAs) on a monthly basis.

Qualifications

Education, Knowledge, and Experience:

Bachelor’s degree in computer science, data science, information technology, or data modeling.

6+ years of experience working in a technology environment

Python, Pandas, and Luigi experience required

Experience with data quality assurance and data quality control processes

Skills:

Fluent English speaker with strong cross-cultural written and verbal communication skills

Outstanding customer-focused support and professionalism

Ability to work across multiple projects simultaneously

Ability to learn quickly and work in a collaborative team environment

A desire to learn new skills and keep up with the changing environment

Strong attention to detail and commitment to accuracy

Disclosures:

Candidates hired for the position must be based in Ethiopia or Kenya. Applicants must be currently authorized to work in Ethiopia or Kenya on a full-time basis. Employment-based visa sponsorship is not available for this position. Depending on project work, qualified candidates may need to meet certain residency requirements.

All qualified applicants will receive consideration for employment without discrimination on the basis of age, race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

AIR adheres to strict child safeguarding principles. All selected candidates will be expected to adhere to these standards and principles and will therefore undergo rigorous reference and background checks.

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