Data Science/Natural Language Processing Analyst- Ipsa 9

Description

Background
UNDP is committed to achieving workforce diversity in terms of gender, nationality and culture. Individuals from minority groups, indigenous groups and persons with disabilities are equally encouraged to apply. All applications will be treated with the strictest confidence.
UNDP does not tolerate sexual exploitation and abuse, any kind of harassment, including sexual harassment, and discrimination. All selected candidates will, therefore, undergo rigorous reference and background checks.

Office/Unit/Project Description

The UN Reform Resolution tasks UNDP to provide countries with an “integrator function” to accelerate progress towards the SDGs by tackling multiple interlinked and interdependent development challenges. The UNDP Global Policy Network (GPN) draws on expertise globally to provide more effective responses to the complex development challenges countries face in achieving the SDGs and responding to crisis in an integrated and coherent manner. Anchored in the Crisis Bureau (CB) and the Bureau for Policy and Programme Support (BPPS), the GPN has the responsibility for developing all relevant policy and guidance to support the results of UNDP’s Strategic Plan, which is aligned with the 2030 Agenda Sustainable Development Goals (SDG).

An SDG Integration Team located with UNDP’s Global Policy Network (GPN) offers a menu of services emphasizing direct short- to medium-term engagements to respond rapidly to requests from country offices for support on national implementation and monitoring of integrated policy solutions, qualitative and evidence-driven analysis for accelerated progress, and knowledge sharing and upscaling of innovative approaches to sustainable development. The team’s work emphasizes the application of evidence-driven data and analytics for SDG implementation and reporting.

In this regard, advances in digital technology are creating data at unprecedented levels of detail and speed, turning the stories of people’s lives into numbers every minute of every day, across the globe. An important focus of the integration work is to complement traditional data (e.g., national statistics,) with new and alternative sources including digital ‘breadcrumbs,’ satellite data, social media to identify emerging trends and gain new perspectives on issues in development.

Under the guidance of the Global Policy Advisor of the SDG Integration Bureau for Policy and Programme Support/Global Policy Network, the Data Science Analyst will assist the team in prototyping, development, deployment, and maintenance of analytical products and services, as applied to reports, publications, project documents and other structured and unstructured data within the organization.
Duties and Responsibilities

Assist in applying natural language processing techniques to support UNDP policy analysis and development challenges.
Support the design, development, and maintenance of automated data processing pipelines at scale.
Perform text data collection, standardization and preparation, exploratory data analysis and visualization to advance the analytical work in the team.
Prototype machine learning models for document classification, sentiment analysis and hate speech detection.
Research and experiment with customized tools using natural language processing and machine learning methods to strengthen the SDG Integration Team’s capabilities.
Collaborate with IT and Thematic teams to design, implement and evaluate text analytics approaches and enhancements.

Institutional Arrangement

The Analyst will work under the guidance and direct supervision of Global Policy Advisor of the SDG Integration team, Bureau for Policy and Programme Support/Global Policy Network and will be responsible for the fulfilment of the scope of work mentioned above.
The Analyst will be part of a growing team responsible for leading programme-related data science work at UNDP.
The Analyst will be responsible for providing their own laptop. Access to cloud resources will be granted when needed.
Given the global nature of UNDP’s work, the Analyst will be expected to be flexible with their availability considering different time zones.

Competencies
Core
Achieve Results: LEVEL 3: Set and align challenging, achievable objectives for multiple projects, have lasting impact
Think Innovatively: LEVEL 3: Proactively mitigate potential risks, develop new ideas to solve complex problems
Learn Continuously: LEVEL 2: Go outside comfort zone, learn from others and support their learning
Adapt with Agility: LEVEL 3: Proactively initiate and champion change, manage multiple competing demands
Act with Determination: LEVEL 3: Think beyond immediate task/barriers and take action to achieve greater results
Engage and Partner: LEVEL 2: Is facilitator/integrator, bring people together, build/maintain coalitions/partnerships
Enable Diversity and Inclusion: LEVEL 2: Facilitate conversations to bridge differences, considers in decision making

Cross-Functional & Technical competencies
Thematic Area Name Definition
Digital & Innovation Data literacy Understand the potential as well as the limitations of using data driven innovation.
Digital & Innovation Data privacy and digital ethics Knowledge of ethical usage of digital technology (e.g. AI, robotics, automation) and data. Ability to assess ethical implications when using, combining or sharing data, when building or implementing AI systems, and when advising on robotisation and automation etc. Ability to design privacy protocols to ensure data is protected and used for legitimate purposes without unnecessary privacy risks.
Digital & Innovation Tech literacy Ability to apply new digital tools or adapting their original use to create new insights, fresh perspectives or develop solutions.
Digital & Innovation Protoyping Ability to make ideas tangible, at low costs early in the innovation process, to test and improve them through iteration.
Digital & Innovation Collective intelligence design Being able to integrate different types of data (real-time, ‘ground- truth’ and novel data) to unlock fresh insights. Understand guidelines and principles around data privacy, ethics and protection.
Required Skills and Experience
Min. Academic Education

Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a similar field.
Bachelor’s degree with additional two years of experience may be considered in lieu of a master's degree.

Min. years of relevant Work experience

For applicants with a master’s degree, at least 2 years of relevant experience in data science are required.
For applicants with a bachelor’s degree, at least 4 years of relevant experience are required.

Required skills and competencies

Proficiency in Python programming is a prerequisite.
Hands-on experience with a standard Python data science stack for NLP, i.e., numpy, pandas, scikit-learn, spacy, gensim, is required.
Proper theoretical understanding of the domain of data science, including, but not limited to, basics of linear algebra, unsupervised and supervised machine learning, and vector space models such as distributed representations is required.
Proven experience in at least two areas of NLP applications, e.g., text classification, information retrieval, semantic search, language modelling, question answering, document summarisation, topic modelling or sentiment analysis, is required.

Desired additional skills and competencies

Proven experience in one of the deep learning frameworks (PyTorch or TensorFlow) is a considerable advantage.
Documented expertise in another data science domain, such as Computer Vision, Geospatial Data Analysis or Tabular Data Analysis, is a considerable advantage.
Hands-on experience with developer tools like Git or Docker is an advantage.
Familiarity with web app development in using Streamlit, Plotly Dash or R Shiny is an advantage.
Familiarity with SQL and NoSQL databases is an advantage.
Experience in social media analysis, including sentiment analysis and hate speech detection, using Twitter API, Meta Graph API or a similar platform is an advantage.
Previous experience working in the international development sector is desirable.

Required Language(s) (at working level)

Excellent written and spoken English (required).
Knowledge of another UN language is an asset.