Background

Guinea-Bissau (GNB) has a history of political and institutional fragility. The economy of Guinea-Bissau is poorly diversified and is highly dependent on agriculture, fisheries and forestry, providing up to 47% of the GDP, with cashew nut as the primary crop. The macroeconomic context of Guinea-Bissau is characterized by low levels of economic growth in recent years, with the country experiencing negative GDP growth of minus 1.7% in 2012, to a GDP growth of 4.6% in 2019 amounting to around 1.35 billion US dollars.  The participation of youth and women in formal economic activities is very low considering that youth, mainly young women, represent 72% of the unemployed population in the country. In addition to the lack of economic opportunities, including social and cultural norms continue to limit their participation in the informal sector, deepening inequality and depriving the country of the potential productivity of a large portion of its human resources. The spread of COVID-19 has exacerbated the existing vulnerabilities of Guinea-Bissau’s economy, as well as, its institutional weakness and public service provision. The economic chock induced, is likely to reverse the economic growth rate as the pandemic has affected exports (especially cashew nuts) and imports, having serious implications on poverty and food security in the country.

The pandemic has further affected main economic actors, like informal workers and MSMEs. Sectors like agriculture, transport and tourism suffered the most. The poor and vulnerable segments of the population, mostly relying on small scale agriculture and natural resources were the most affected. The adverse impact of COVID-19 on MSMEs is quite severe. According to a recent study commissioned by UNDP to assess the impact of COVID-19 on MSMEs, the approximate average duration of firm closure was 143.1 days and most firms had difficulties getting supplies due to the closure of borders. Exporting firms experienced a sharp decline in exports.  Lack of data and policy-oriented studies to inform public choice and guide government policies hinders the formulation of coherent recovery plans which could further excavate the crisis and lead to conflict.

UNDP country office following the transition of the UNIOGBIS recognizes the Socio-Economic pillar as one of its peace-building priorities to prevent conflict and advance on economic transformation as a key component to support increased livelihood opportunities, social cohesion, the social contract and position UNDP as a key actor in the country and is committed to support the government of Guinea Bissau and its population to strengthen Socio-Economic Recovery Efforts and build Resilience through the pursuit of inclusive and economic green growth interventions that leaves no one behind and accelerate progress towards SDGs. 

To this end, UNDP Strategic and Economic Unit has developed an umbrella framework to encompass several ongoing projects adhering to the above objective of the transition and regional/global strategic engagements and will carry an integrator role and stand accountable to implement the Economic Recovery and Resilience work of the United Nations, its partners and relevant stakeholders. In light of the Strategic and Economic Unit’s increased portfolio, mandate and key role within the transition context, the following support is requested a Data Analyst.

Duties and Responsibilities

The Consultant, hired as Data Analyst, under the direct supervision of the head of the Strategic and Economic Unit and will perform the following functions:

Summary of key functions:

• Data Management and Analysis
• Data Visualization, Reporting and Application
• Technical Support
• Identify key data gaps Economic Recovery and Resilience tracking in Guinea-Bissau, with particular emphasis in region with highest multidimensional poverty index (Gabu, Oio Bafata, and Bolama) and islands region (Bolama), and with a particular emphasis on primary data
• Develop a process for and understand primary data gathering (e.g. designing and conducting periodic perception surveys)
• Identify and integrate additional primary and secondary data into analysis for programming and policy as required by the unit, adressing the evolving needs
• Develop a platform for online information management and ensure content is current, comprehensive, and follows relevant metadata standards;
• Understand, document, and ensure the quality of high-value data for accuracy, consistency and comparability, and advise on the applications of these
• Support the design, development and management of databases, spreadsheets and other data tools
• Contribute with new ideas for improving the data engine, quality, and timeliness of current issues
• Suport the setting up of Evidence labs, capacity transfer plan and Evidence based research with relevant UNDP Partners
• Build a network consisting of local and international organizations that apply data science to policymaking and programming
• Support fundraising efforts by producing insightful visulation of data/infographics
• Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems, organize large datasets to get actionable insights
• Provide other support and assistance as required

Deliverables

• A methodology with a workplan
• Scope and prepare an engagement plan for local and international organizations that apply data science to policymaking and programming
• A finalized Crisis Risk Dashboard for Guinea Bissau
• A finalized Data Science Roadmap for the Strategic and Economic Unit

Terms of Payment:

Monthly upon completion and satisfactory performance of the assignment, as agreed with the supervisor at the beginning of each month.

Competencies

Core

• Innovation: Ability to make new and useful ideas work
• Leadership: Ability to persuade others to follow
• People Management: Ability to improve performance and satisfaction
• Communication: Ability to listen, adapt, influence and transform
• Delivery: Ability to get things done while exercising good judgment

Technical/Functional

• Excellent verbal and written communication skills
• Strong track record in data science and related fields
• Working knowledge of data analytics, cloud computing, business intelligence and visualizations, Agile and DevOps methodologies
• Working knowledge of programming language including Python, R, and front-end frameworks
• Ability to build strong and sustainable relationships and capability to interact at all levels within the organization.
• Ability to deliver in a high-pressure environment
• Ability to support the development of digital initiatives to support business objectives
• Strong conceptual thinking to develop new strategies & innovative projects
• Self-motivated and able to work with a high degree of autonomy
• Fully committed and motivated to achieve the aims of UNDP and the SDGs

Education

Master’s Degree in fields related to Computer Science, Management Information Systems, Data Science, Statistics or equivalent field.

Experience

• At least 3 years of professional experience in data management, applied science, statistics, information systems, or another analytical field
• Experience in data analytics and programming in languages such as R or Python
• Experience in supporting Digital Product development.
• Have experience working with UN agencies and governmental entities, especially on the development of statical capacity, methodologies, and frameworks.
• Experience working in countries with weak governance institutions and scarce data.
• Experience working in SIDS, LDCs and/or African countries are preferred.

Language

Excellent verbal and writing communication skills (fluency) in English and Portuguese/ or French

Application procedure

The application package containing to file (one technical proposal and one financial proposal).

Technical proposal

The technical proposal will contain the following (to be uploaded as one pdf file):

• A brief description of why the applicant considers her/himself the most suitable for the assignment; and
• Personal CV or P11 indicating all past experience from similar projects and specifying the relevant assignment period (from/to), as well as the email and telephone contacts of at least three (3) professional references.

Financial proposal

Scope of Price Proposal and Schedule of Payments:

• Financial proposals must be expressed as “an all-inclusive daily fee” in USD.
• Payment will be made upon submission of a certificate of payment request, indicating outputs achieved and days worked to be verified and cleared for payment by the supervisor.

Travel

If travel is required, the travel costs will be covered by UNDP in accordance with UNDP rules and procedures

Criteria for Selection of the Best Offer:

The selection of the best offer will be based on a Combined Scoring method – where the technical evaluation (desk review) will be weighted a maximum of 70% and combined with the price offer which will be weighted a maximum of 30%. The 70% rating shall be based on how well the Offer or meets the minimum qualifications/competencies described above.

Evaluation Criteria

The technical evaluation will be based on the following criteria with the corresponding points (out of a total 70 points):

• Master’s Degree in fields related to Computer Science, Management Information Systems, Data Science, Statistics or equivalent field (25 points)
• At least 3 years of professional experience in data management, applied science, statistics, information systems, or another analytical field (20 points)
• Experience in data analytics and programming in languages such as R or Python (15 points)
• Experience in supporting Digital Product development (15 points)
• Have experience working with UN agencies and governmental entities, especially on the development of statical capacity, methodologies, and frameworks (10 points)
• Experience working in countries with weak governance institutions and scarce data (10 points)
• Experience working in SIDS, LDCs and/or African countries are preferred (5 points)

Financial Evaluation

Only applicants with a minimum of 45 points on their technical proposal will be considered for financial evaluation. The following formula will be used to evaluate financial proposal: p = 30 (µ/z),

Where

• points for the financial proposal being evaluated
• price of the lowest priced proposal
• price of the proposal being evaluated

The contract will be awarded to the applicant who receives the highest combined score.