Data Science/ML Analyst - IPSA 9


Location : Home-based
Application Deadline :26-May-22 (Midnight New York, USA)
Time left :2d 6h 56m
Type of Contract :IPSA (Regular)
Post Level :IPSA-9
Languages Required :
English  
Duration of Initial Contract :6 months
Expected Duration of Assignment :6 months with possibility of extension


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.


Background

Instructions to Applicants: Click on the "Apply now" button. Input your information in the appropriate Sections: personal information, language proficiency, education, resume and motivation. Upon completion of the first page, please hit "submit application" tab at the end of the page. Please ensure that CV or P11 and the Cover letter are combined in one file.

The following documents shall be required from the applicants:

Personal CV or P11, indicating all past positions held and their main underlying functions, their durations (month/year), the qualifications, as well as the contact details (email and telephone number) of the Candidate, and at least three (3) the most recent professional references of previous supervisors. References may also include peers.

A cover letter (maximum length: 1 page) indicating why the candidate considers him-/herself to be suitable for the position.

Managers may ask (ad hoc) for any other materials relevant to pre-assessing the relevance of their experience, such as reports, presentations, publications, campaigns or other materials.

 

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 lead on the development, training and testing of text analytics/Natural Language Processing (NLP) of reports, project information and other data for the organisation.

 

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 given access to relevant information necessary for the execution of the tasks under this assignment. The
  • The Analyst will be responsible for providing her/his own laptop.
  • Given the global nature of UNDP’s work, the Analyst is expected to be reasonably flexible with his/her availability for such consultations taking into consideration different time zones


Duties and Responsibilities

Scope of Work

  1. Assist in the mapping and analysis of current context by mainstreaming Machine Learning (ML) models to support UNDP policy analysis and development challenges;
  2. Build and deploy Natural Langue Processing (NLP)/ Machine Learning (ML) models for portfolio and project analytics, and more particularly for the SDG Integration Team’s work on SDG Acceleration Diagnostic, thematic taxonomy implementation and others as needed;
  3. Design and implement data quality procedures to support data quality management activities such as the implementation of data pipeline for Natural Langue Processing (NLP)/ Machine Learning (ML) models to ensure high quality analytics required for various purposes;
  4. Research and experiment customized tools using Natural Langue Processing (NLP)/ Machine Learning (ML) methods to strengthen the SDG Integration Team’s data collection, and analysis, capabilities;
  5. Collaborate with IT and Thematic teams to discuss, design, test and implement text analytics approaches and enhancements;


Competencies

Core

Achieve Results:

LEVEL 2: Scale up solutions and simplifies processes, balances speed and accuracy in doing work

Think Innovatively:

LEVEL 2: Offer new ideas/open to new approaches, demonstrate systemic/integrated thinking

Learn Continuously:

LEVEL 2: Go outside comfort zone, learn from others and support their learning

Adapt with Agility:

LEVEL 2: Adapt processes/approaches to new situations, involve others in change process

Act with Determination:

LEVEL 2: Able to persevere and deal with multiple sources of pressure simultaneously

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 analysis

Ability to extract, analyse and visualizedata (including Real-Time Data) to form meaningful insights and aid effective decision making

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

Data collection

Being skilled in Data Sorting, Data Cleaning, Survey Administration, Presentation and Reporting including collection of Real-Time Data (e.g. mobile data, satellite data, sensor data).

Digital & Innovation

Data engineering

Ability in programming languages such as SQL, Python, and R, be adept at finding warehousing solutions, and using ETL (Extract, Transfer, Load) tools, and understanding basic machine learning and algorithms.

Digital & Innovation

Data governance

Knowledge of data science, skills to develop data management tools, organize and maintain databases and operate data visualization technologies

Digital & Innovation

Data storytelling and communications

Skilled in building a narrative around a set of data and its accompanying visualizations to help convey the meaning of that data in a powerful and compelling fashion.

Digital & Innovation

Geospatial analysis

Skilled in techniques which study entities using their topological, geometric, or geographic properties.


Required Skills and Experience

Min. Education requirements

  • Master’s degree in Computer Science or relevant field. Field of study with a focus on Natural Language Processing or Machine Learning, considered an asset;
  • Bachelor’s degree with additional two years of of experience may be taken into consideration in lieu of Master’s degree.

Min. years of relevant work experience

  • Master’s degree with 2 years’ relevant experience in data science with a focus on NLP or Machine Learning, or Bachelor’s degree with 4 years’ relevant experience

Required  skills

  • Demonstrated experience with NLP/ML Entity Extraction, Topic Modeling, Text Classification;
  • Experience working with NLP/ML libraries (e.g. transformers, spacy, scikit-learn, rasa, SparkNLP);
  • Highly skilled in the use of Python.

Desired skills in addition to the competencies covered in the Competencies section

  • Experience with other programing languages (e.g. Java, JavaScript);
  • Experience with one of the Deep Learning Frameworks such as TensorFlow, Torch, MXNet, etc;
  • Skills in analysis of geostaptial data;
  • Understanding of the fundamental of Transformer Models and experience of implementing one at the academic or industrial level;
  • Previous experience working in the international development sector;

Required Language(s)

  • Fluency in English;
  • Knowledge of another UN language considered an asset.



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