The International Initiative for Impact Evaluation (3ie) promotes evidence-informed equitable, inclusive and sustainable development. We support the generation and effective use of high- quality evidence to inform decision-making and improve the lives of people living in poverty in low- and middle-income countries (LMICs). We provide guidance and support to produce, synthesize and quality-assure evidence of what works, for whom, how, why and at what cost. 3ie is registered as a non-governmental organization in the United States. It has offices in New Delhi, London and Washington, DC.
3ie seeks one or more experts to help advance our efforts to improve the timeliness and efficiency of our individual evidence synthesis projects, as well as develop an infrastructure of continuous evidence surveillance of the international development literature. This will be achieved through (1) improved procedures for managing and reformatting large datasets, to facilitate reuse of data across projects, and (2) expanded use of machine learning models, including by automating information extraction and classification of academic articles. We are open to hiring one person with all relevant skills or multiple people with specialized expertise for particular types of tasks.
- Conduct an audit of 3ie workflows for systematic reviews, evidence gap maps and the Development Evidence Portal to identify areas with potential for machine learning and data science to improve processes and efficiencies. The task includes producing a short report with clear recommendations for immediate, medium- and long-term action, together with associated costs and timelines.
- Data science tasks:
a. Establish and implement procedures for management of large datasets, including organization of data repositories, managing access privileges, version control, and maintaining clean/“tidy” data.
b. Build and maintain Kibana dashboards for ElasticSearch databases.
- Machine learning tasks:
a. Build, test, and refine machine learning models using state-of-the-art NLP approaches (e.g., BERT models), and establish protocols for incorporating use of these models into existing workflows. In particular, models will be used for:
i. Text classification.
ii. Automatic extraction of information from full-length academic articles into a standardized template.
- Business development tasks:
a. Contribute to bids for contracts by writing sections explaining how machine learning/automation will be used to save time and reduce costs.
- Other duties as assigned.
Qualifications and key competencies
- Relevant university degree and post graduate training in computer science, statistics, mathematics, economics, information sciences, or other related quantitative field
- In-depth and up-to-date knowledge of state-of-the-art methodologies for (semi-) automation of key systematic review processes
- Track record of applying data science and machine learning to improve processes and efficiencies of systematic review methodologies, preferably in the social sciences
- For machine learning specialist:
o Advanced experience in using Python or R for Machine Learning
- For data science specialist:
o Advanced experience in ETL (Extract, Transform, Load) pipeline for effective database management
o Advanced experience in planning, formulating, and executing Kibana dashboards
This position is fully remote and candidates should be willing to maintain core hours conducive to working with colleagues in the Delhi, London and Washington offices. 3ie is an equal-opportunity employer committed to equality and diversity. We do not discriminate based on sex, age, religion, ethnicity, caste, sexual orientation or for being differently abled. We particularly encourage ethnic minorities and differently-abled persons to apply.
Terms of employment
Candidates should be available to start work at the earliest. The consultant will be paid a day rate commensurate with experience and the duration and number of days included in the contract will depend on the aspects of the ToR covered by the consultant.
Our policies and procedures reflect our commitment to safeguarding children and vulnerable adults from abuse. We follow a zero-tolerance policy for any form of bullying or harassment in the workplace.
How to apply
Please apply by e-mail to firstname.lastname@example.org. Please include ‘SRO ML specialist' in the subject. The applicant must provide, at a minimum*, the following:
- Cover letter, not exceeding one page, highlighting your qualifications and experience relevant to the terms of reference
- Curriculum vitae (not to exceed four pages), including links to your relevant GitHub portfolio and/or recent projects you have completed
- Expected daily rate
- Contact information for three professional references
* Incomplete applications will not be considered.
Applications will be accepted and reviewed on a rolling basis until the position is filled. We will contact only shortlisted candidates.