Data Scientist

The UNDP Strategic Plan embraces the complexity of development and commits the organization to helping countries find faster, more durable solutions to achieve Agenda 2030. Important development trends like urbanization, climate change, and rising inequalities pose significant challenges on our path to achieve the 2030 agenda of achieving the Sustainable Development Goals (SDGs). 

UNDP has begun incubating a few strategic initiatives aimed at ensuring UNDP is ‘fit for purpose’ to deliver a new generation of solutions in line with the challenges the world faces. One such key strategic initiatives is the UNDP Accelerator Lab Network which operates as part of UNDP’s sustainable development offering. 

The Accelerator Lab Belarus is the part of the largest and fastest learning global network on development challenges. 92 labs have already been set up in 116 countries embedded within UNDP’s global architecture and country platforms. We use the power of the crowd, machine learning and distributed decision making to support partners to understand problems, develop new solutions, promote more inclusive decision making, and provide better oversight of what is done. We identify grassroots solutions and stretch their potential to accelerate development. We apply experimentation closely with government partners to grow this as a mode of operating to reduce costs of large-scale public sector reforms. Experimentation helps us learn whether particular assumptions are accurate before deploying solutions at scale, especially in the rapidly evolving contexts that often dominate development progress. 

To achieve its goals, the Lab is looking for a Data Scientist to apply data mining techniques to create actionable insights from a broad range of structured and unstructured data that is growing rapidly in scale.  The Data Scientist will be responsible for the acquisition, analysis and visualization of data from a variety of sources in order to i) help understand developing challenges, ii) detect and highlight patterns that could indicate how people are coping with emerging hardship, and iii) gather evidence of changes in behavior and perception correlated with public sector policies and programmes. 

• Define, design and implement research projects harnessing data to improve both understanding of population behavior, needs, and vulnerabilities as well as capacity to monitor and evaluate the impacts of public sector policies and programmes;  
• Study, explore, and evaluate new and existing data sources to determine their effectiveness and accuracy for use in decision making, and assess their suitability for actionable output. Provide data-driven recommendations to stakeholders; 
• Analyse relevant data (including web-based, open and/or official data) using data science methods such as supervised and unsupervised machine learning, natural language processing or network science; identify target datasets to support our work; define data acquisition strategy; 
• Liaise with technology stakeholders to access infrastructure, software and services needed to develop and deploy data science products; 
• Design and build predictive data science products, such as visualizations, models or AI/ML algorithms for initial simulations or prototypes and subsequent ingestion into mainstream software applications; 
• Promote use of data science solutions by showcasing the products to stakeholders; plan the dissemination of data products to key stakeholders, raise awareness of available data products; 
• Contribute to short- and long-term planning of the organization and assist in identifying threats and opportunities to the successful implementation of mandates; 
• Develop processes and tools to monitor and analyze model performance and data accuracy; 
• Perform other related tasks as assigned by the immediate Supervisor.
   

• Job knowledge and technical expertise: knowledge of data analysis life cycle from ingest and wrangling to analysis and visualization to present findings; good analytical and problem-solving skills, ability to build new products and drive new approaches; convey complex / difficult data science topics to clients in a relatable manner; takes pride in the work for the organization and understands the impact that can be brought into the organization by allowing data-driven and evidence-based decisions; demonstrates professional competence and mastery of subject matter; keeps abreast of available technology; understands applicability and limitation of technology to the work of the office; actively seeks to apply technology to appropriate tasks; shows willingness to learn new technology; delivers outputs for which one has responsibility within prescribed time, cost and quality standards; operates in compliance with organizational regulations and rules. 
• Building partnerships: considers all those to whom services are provided to be “clients” and seeks to see things from clients’ point of view; establishes and maintains productive partnerships with clients by gaining their trust and respect; identifies clients’ needs and matches them to appropriate solutions; monitors ongoing developments inside and outside the clients’ environment to keep informed and anticipate problems; meets timeline for delivery of products or services to client. 
• Communication/teamwork:  speaks and writes clearly and effectively; tailors language, tone, style and format to match audience; demonstrates openness in sharing information and keeping people informed; works collaboratively with colleagues to achieve organizational goals; is willing to learn from others.   
• Creativity: actively seeks to improve programmes or services; offers new and different options to solve problems or meet client needs; promotes and persuades others to consider new ideas; takes calculated risks on new and unusual ideas; thinks “outside the box”; takes an interest in new ideas and new ways of doing things; is not bound by current thinking or traditional approaches. 
• Delivery:  develops clear goals that are consistent with agreed strategies; identifies priority activities and assignments; adjusts priorities as required; allocates appropriate amount of time and resources for completing work; foresees risks and allows for contingencies when planning; monitors and adjusts plans and actions as necessary; uses time efficiently;  applies judgment in the context of assignments given, plans own work and manages conflicting priorities.  
• Commitment to Continuous Learning: keeps abreast of new developments in own occupation/profession; actively seeks to develop  professionally and personally; contributes to the learning of colleagues; shows willingness to learn from others; seeks feedback to learn and improve.
   

• University degree in data science, computer science, information management, statistics, public information, management or a related field. 
• At least 2 years of professional experience; 
• Work experience in startups is an asset; 
• Experience of data Science tools such as Jupyter, Matlab, Knime, SPSS, SAS, or similar Statistical Programming Languages such as R, Python, Javascript or related is desirable; 
• Intermediate level of English, proficiency in Russian.

Important applicant information

All posts in the SC categories are subject to local recruitment.

Applicant information about UNDP rosters

Note: UNDP reserves the right to select one or more candidates from this vacancy announcement.  We may also retain applications and consider candidates applying to this post for other similar positions with UNDP at the same grade level and with similar job description, experience and educational requirements.

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