Data Analyst in Deutschland bei World Food Programme

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encourages qualified candidates to apply irrespective of race, color, national origin, ethnic or social background, genetic information,

gender, gender identity and/or expression, sexual orientation, religion or belief, HIV status, physical or mental disability.

Job Title: Data Analyst (5 posts)

Type of Contract: Regular Consultant level I

Division: CBT / Cash-Based Transfers Division

Duty Station (City, Country): Munich, Germany

Duration: 11 months

BACKGROUND AND PURPOSE OF THE ASSIGNMENT:

The United Nations World Food Programme (WFP) is the world’s largest humanitarian organization, saving lives in emergencies and using food and cash assistance to change lives and empower people to meet their essential needs. WFP does this both through direct programming as well as by supporting governments on their national pathways toward the Sustainable Development Goals (SDGs), in partnership with multiple stakeholders. WFP is the largest cash actor in the humanitarian community: WFP transferred over US$3.3 billion to 56 million people across 72 countries in 2022.

WFP endeavours to reach as many people in need as possible utilising available resources. This means making sure that assistance reaches intended people while preventing or detecting the possible divergence of entitlements (food and cash). WFP either collects personal data from people directly or receives data from partners to enrol people into assistance programmes, and then continually verifies people to make sure that assistance is reaching the right individuals and families.

WFP Country Offices deliver assistance to beneficiaries through a variety of digital platforms and service providers. WFP works in partnership with several commercial Financial Service Providers (FSPs), including banks, micro-finance institutions, mobile money operators and money transfer agents, in addition to using WFP’s own delivery platform, SCOPE. One of WFP’s corporate objectives is to increasingly digitize the delivery of both in kind and CBT assistance, to achieve greater efficiencies and provide greater accountability and traceability of assistance delivered. Therefore, WFP seeks to build its corporate capacity to centrally receive, store, process and analyze digital operational data for the purpose of promoting accountability, controls, and efficiencies as part of cash-based transfers and in-kind assistance. There is also the opportunity to better inform WFP’s programme design through the analysis of digital data emanating from operations.

Several challenges exist in streamlining digital analysis globally, including the tasks of receiving and maintaining varied operational data from different systems and modalities, processing and generating meaningful analysis of data, and ensuring that data privacy and security standards are upheld. The Cash Data Services unit within the Program division plays a crucial role in supporting the implementation of CBT and in-kind assistance programs, offering end-to-end or standalone data services to meet corporate identity management (IDM) and reconciliation standards.

To achieve the objectives outlined above, WFP is recruiting Data Analysts to be part of the Cash Data Services team established in the CBT Division, in support of WFP’s CBT operations globally.

WFP is committed to an accessible, inclusive recruitment process. Please contact us at global.inclusion@wfp.org to advise us of any disability related reasonable accommodation

or accessibility requests you may have. A member of the reasonable accommodation team will contact you to confidentially discuss your needs

ACCOUNTABILITIES AND RESPONSIBILITIES:

• In collaboration with central CBT teams and field stakeholders, support the analysis of business requirements covering the design and development of data transformation and reports, focusing on assurance controls such as identity management, transfer reconciliation, and anomaly detection.
• Develop data models and write data-transformation code to validate assumptions and prototype automated controls.
• Provide technical specifications to data engineers for implementing data-transformation requirements as automated data-pipelines.
• Apply data-science techniques to detect data quality issues and operational anomalies.
• Contribute to the analysis of maturity gaps in IDM and Cash Assurance, identifying areas for improvement and supporting the development of solutions to address identified gaps.
• Write