Consultant (Data Scientist) at UNDP

Location: Home Based, Nigeria
Additional Category: Sustainable Development and Poverty Reduction
Type of Contract: Individual Contract
Post Level: International Consultant
Starting Date: Date when the selected candidate is expected to start -17-Aug-2020
Duration of Initial Contract: 35 Working Days
Expected Duration of Assignment: Three(3) Months

Background

• UNDP Nigeria has established a Knowledge Hub to enhance its ability to make timely and evidence-based interventions, particularly in areas of conflict prevention and human security. A new type of ‘development intelligence gathering’, i.e. continuous monitoring and data collection, is crucial to inform UNDP’s work for early warning, adjust interventions to maximize preventive efforts and initiate new thematic approaches. Trend analyses and ad-hoc policy briefs will also inform interventions of UNDP’s development partners in this field. Through harnessing the potential offered by both old and new sources of data, it is UNDP’s hope that the accuracy and precision of its development responses are increased and a strong foundation for meaningful public policy making, efficient resource allocation and effective public service delivery is created.
• The ultimate objective of the Knowledge Hub is to harness data, including real time data, for development through providing evidence-based intelligence that can be translated to meaningful policies and planning for development impact.
• Given the current global coronavirus pandemic, the socio-economic fallout for Nigeria is potentially monumental, with visible pressure on the federal budget already showing. What started as a health crisis - with grave impact on populations, has also within days become a real economic crisis, and will soon turn into a massive fiscal challenge. With over 90% reliance on the oil sector for government export revenue, oil prices have already declined by 55% since the advent of the COVID-19 and 48% monthly decline are expected if the pandemic persists. This would affect the government’s ability to implement all development interventions and impact the ability to respond to the crisis. The global economic downturn will exacerbate affects on the Nigerian economy. With little in the way of social safety nets and few public resources to help ease the fallout, the economy risks collapsing. The Government may also expose itself to a debt crisis if forced to borrow large sums of money.  Revenues are reportedly down by 48%.
• The secondary impact of the pandemic in the country is expected to be grave. There is a risk of social tensions and increases in criminality. Unemployment is expected to increase significantly as a result of economic pressures. Further, already existing social tensions between some communities such as host communities/IDP’s; religious groups; herders/ farmers may escalate. The health crisis could also trigger knock-on emergencies related to education and food security, disrupt the large-scale humanitarian response to the conflict in the North-eastern part of the country, and set back already stressed broader human development efforts.
• In response, UNDP will support the Government of Nigeria to re-imagine innovative approaches to respond to COVID-19 while ensuring sustainable recovery of national and state economies, livelihoods and well-being of citizens after the crisis.
• The ultimate goal of UNDP’s COVID-19 support to the Government is a recovery strategy to re-establish the conditions for a quick recovery and return to a path of economic growth, improved social contract, and overall human development that can foster more inclusive societies in the future. Preparedness and mitigation measures being put in place will need foresight and proactive thinking at policy and practical levels to integrate innovative post-COVID-19 recovery approaches. A key foundation for this is availing rapid intelligence gathering, R&D support and Data Innovation, with systematic use of sex-disaggregated data to provide the much-needed socio-economic trend analysis to compliment epidemiological analytics that will frame the risk stratification in society and across sectors with policy actions for the immediate long term.
• As part of this support, UNDP Nigeria’s Knowledge Hub has been tasked to provide analytical support ensuring that potential socio-economic indicators are monitored and fallouts are identified using various datasets and statistical and data analysis and models to provide this insight and monitor the trends of the secondary impact of COVID-19 as well as analyses that will shed light on economic recovery strategies. The IC will work with the UNDP team and will support the modelling, as well as other socio-economic projections, were relevant.

Duties and Responsibilities
The IC will undertake the following tasks:

• Support the development of a socioeconomic dashboard to monitor trends that will inform UNDP Nigeria’s recovery efforts. The IC will work closely with the Knowledge Hub team to develop a dashboard displaying visualisation that tracks and monitors a range of socio-economic indicators related to the impact of COVID-19 pandemic in Nigeria.
• Support data analytics and projections in the area of energy and mobility. The IC will work closely with the Knowledge Hub to develop models and projections using various statistical methods, including machine learning techniques, to develop robust predictive models that monitor and estimate the distribution of the energy infrastructure within the country as well in the development of mobility proxies.

Expected Outcome/ Deliverables?
The Consultant will be expected to deliver the following:

• In close collaboration with the UNDP team develop and deploy a socioeconomics dashboard that monitors vital socioeconomic indicators and trends;
• Support two other socio-economic related analytics projections that will inform recovery efforts in the country.

The Consultant will work under the direct supervision of the UNDP Nigeria Knowledge Hub Coordinator

Required Skills and Experience

• Master's degree or equivalent in Quantitative Methods, Applied Statistics, Computer Science or other relevant fields
• At least 8 years proven experience conducting big data analytics, predictive modelling using various statistical methods, including machine learning methodologies and tools
• Experience in publication of peer-reviewed statistical research using various dynamic and statistical methods
• Proven experience in using big data, machine learning methods and predictive analysis in human mobility, particularly in urban spaces
• Proven experience with backend and frontend development of dashboards and visualisation applications
• Proven experience in conducting various methods of statistical analysis including machine learning, predictive modelling;
• Ability to lead the statistical analysis and to combine with broader analytical trends and observations. This work includes explaining and applying findings and recommendations following the assessment;
• Proven experience writing procedure documents and analysis reports for an international audience.
• Excellent command of English.

Languages Required:

• English.

Competencies:

• Specialisation in employing various big data methods in the field of human mobility and/or urban dynamics
• Proven expertise in both front end and back end development experience
• Ability to multi-task and coordinate several assignments;
• Shows pride in work and in achievements;
• Excellent analytical and organizational skills;
• Motivated by professional rather than personal concerns;
• Ability to show persistence when faced with difficult problems or challenges;
• Ability to remains calm in stressful situations.

Selection Criteria

• Master's degree or equivalent in Quantitative Methods, Applied Statistics, Computer Science or other relevant fields – 10 points
• At least 8 years proven experience conducting big data analytics, predictive modelling using various statistical methods, including machine learning methodologies and tools – 25 points
• Experience in publication of peer-reviewed statistical research using various dynamic and statistical methods – 15 points
• Proven experience in using big data, machine learning methods and predictive analysis in human mobility, particularly in urban spaces – 25 points
• Proven experience with backend and frontend development of dashboards and visualisation applications – 25 points.