Application deadline: 30 March 2020
Background Information -IAIG
Internal Audit and Investigations GroupThe purpose of the Internal Audit and Investigations Group is to provide independent and impartial assurance and advice to improve UNOPS operations. The group reports on the use of resources administered by UNOPS and the effectiveness of internal control systems; and enhances the effectiveness of risk management, control and governance processes. Furthermore, the Internal Audit and Investigations Group leads the Executive Director’s investigations into alleged fraud, corruption, waste of resources, abuse of authority or other misconduct and violations of UNOPS regulations, rules and administrative instructions.
The data analyst will work under the general guidance and supervision of the Manager of Internal Audit Section. The individual will conduct Data Analysis work for the Internal Audits and Investigations. This involves Data Analysis work, such as but not limited to:
Contribute to building machine learning models to detect high-risk activities like fraudulent transactions or high-risk entities like shell vendors.
Apply statistics, data mining and machine learning techniques to answer audit and investigations questions and develop new ways and models for detecting red-flags and generating insights for IAIG.
Communicate orally and in writing, data analytics findings/conclusions and make presentations to the audit team as required.
Advanced university degree (Masters) in Computer Science, Quantitative Economics, Econometrics, Mathematics, Statistics, Operations Research, Financial Engineering or other quantitative fields of study is required.
Advanced university degree (Masters) in a business or social science field with strong competence and practical experience in applied data science shall also be considered.
First level university degree (Bachelors) in above related fields and 2 additional years of relevant experience may be accepted in lieu of the advanced university degree.
Minimum of 2 years of relevant experience in developing, testing and productionizing machine learning methods - (clustering, regression, optimization, neural networks etc), deploying and maintaining models in production environments - preferably GCP environment is required
A minimum of 2 years experience in a data analysis role is required
Knowledge and experience using SQL, Python, Jupyter and/or Flask is required.
Experience with packages such as Numpy, Scipy, pandas, scikit-learn and/or
networkx is highly desired.
Contract type, level and duration
Contract type: International Individual Agreement - Retainer
Contract level: IICA 1
Contract duration: 1 year, renewable upon satisfactory performance and budget availability.
*** Please note that this is note a full time position but it is a part-time retainer.
For more details about the ICA contractual modality, please follow this link:
About the Organization
UNOPS is an operational arm of the United Nations, supporting the successful implementation of its partners’ peacebuilding, humanitarian and development projects around the world. Our mission is to help people build better lives and countries achieve sustainable development.
UNOPS areas of expertise cover infrastructure, procurement, project management, financial management and human resources.
Working with us
UNOPS offers short- and long-term work opportunities in diverse and challenging environments across the globe. We are looking for creative, results-focused professionals with skills in a range of disciplines.
With over 4,000 UNOPS personnel and approximately 7,000 personnel recruited on behalf of UNOPS partners spread across 80 countries, our workforce represents a wide range of nationalities and cultures. We promote a balanced, diverse workforce — a strength that helps us better understand and address our partners’ needs, and continually strive to improve our gender balance through initiatives and policies that encourage recruitment of qualified female candidates.
Work life harmonization
UNOPS values its people and recognizes the importance of balancing professional and personal demands.