Data Scientist – Data Science for Social Good – Nova SBE/BIPD/2021/03 – Research Fellowship

Website Nova SBE Data Science Knowledge Center

A call for applications for a Research Fellowship – Data Scientist is open at Nova School of Business and Economics (NOVA SBE) under the Project “Data Science for Social Good” (Data for Change), under development by the Data Science Knowledge Center, funded by Nova SBE under the Social Equity Initiative (SEI), with the following conditions:

Main field: Data Science, Data Analytics, Data Visualization

Admission Requirements:

1.       Hold a doctoral degree, obtained in the three years prior to the date of submission of the fellowship application (mandatory).

2.       Have conducted the research work that led to the attribution of a doctoral degree in an institution other than the host institution (Nova School of Business & Economics) (mandatory).

3.       Have a background in Data Analytics, Data Science, Computer Science, Statistics, Mathematics, Engineering or similar (preferred).

4.       Have programming experience in any language (SQL and Python preferred. Please provide a link to your GitHub account if possible) (preferred).

5.       Have taken additional courses or experiences in Data related subjects if their background is not directly related to Data Analytics/Data Science/Statistics (preferred).

6.       Experience working with AWS (preferred).

7.       Demonstrated interest in social good (e.g., worked with or for a non-profit/ impact driven organization) (preferred).

Work Plan:

The Nova SBE Data Science Knowledge Center (DSKC) aims to advance the knowledge about data-driven decision-making and its application in society. Our position in a school of business and economics, and our understanding of social sciences, technology, programming, and statistical methods, allow us to bridge the gap between organizations and technology that generates processes and uses data for creating impact.

Currently, DSKC’s members are working on projects and research in the applications of Data Science for Social Good, Data Driven Policy, Decision-Making, Understanding Human Behaviour, and Marketing and Economics (Theory and Measurement).

By joining the DSKC, you will be part of several project teams, that can be composed of a Principal Investigator (Faculty member), a Project Manager, a Web Developer, and Data Scientists/ Analysts/ Consultants as needed, considering the project goals.

Main responsibilities:

1.     Collaboration in defining the scope and objectives of the project (scoping & business understanding phases of the project);

2.     Collaboration in defining deliverables, acceptance criteria and impact measurement metrics;

3.     Development of data validation, preparation, and guarantee the data understanding through an Exploratory Data Analysis (EDA);

4.     Development of machine learning models (experimentation, evaluation and selection of models);

5.     Development and consolidation of project’s pipeline;

6.     Development of machine learning Bias and Fairness analysis;

7.     Collaboration in the development of applications/ tools to present the machine learning model’s results;

8.     Collaboration on the preparation of the project’s consolidated documentation (Project Charter, EDA, Technical Report, Users’ guide, GitHub repository, among other).

The researcher will attend daily check-ins with the team, weekly status meetings internal and external, as well as any other meeting under the projects in which he/ she is participating.

Applicable Law and Regulations:

Research Fellowship Holder Statute (“Estatuto do Bolseiro de Investigação Científica”), approved by Law n.º 40/2004, of 18th August, subsequently amended and republished by Decree-Law n.º 202/2012, of 27th August, updated in accordance with Decree-Law n.º 233/2012, of 29th October, Law n.º 12/2013, of 29th January, and with Decree-Law n.º 89/2013, of 9th July, updated in accordance with Decree-Law n.º 123/2019, of 28th August. Fellowship Regulations of Nova SBE, approved by FCT, I.P. by Dispatch of 16th April 2014 and Regulations for Studentships and Fellowships of the FCT, I.P. Fellowship Regulations of Nova SBE, approved by FCT, I.P. by Dispatch of 16th April 2014 and Regulations for Studentships and Fellowships of the FCT, I.P., approved by Regulation 950/2019, of 16th December.

Working place:

The research will be conducted at NOVA SBE under the scientific supervision of Professor Leid Zejnilovic (or remotely, according to the Covid-19 legislation).

Duration of the Fellowship:

The fellowship will have a duration of 12 months, with possibility of renewal for the length of the project, subject to periodic reviews. The fellowship will be awarded on an exclusive basis, as stated in Regulations for Studentships and Fellowships of FCT, I.P.

Monthly allowance:

The fellowship amounts to €1646, according to the table of monthly stipends available in the Regulations for Studentships and Fellowships of FCT, I.P. (

Selection criteria:

The selection will be carried upon the evaluation of the CV (20%), motivation letter (10%), interviews (35%) and a data science challenge (35%).

Selection Committee:

Leid Zejnilovic – Chairman (Assistant Professor)

Susana Lavado – Effective member (Senior Data Scientist)

Bruna Riboldi – Effective member (Project Manager)

Lénia Mestrinho – Substitute member (Executive Director Nova SBE Data Science Knowledge Center)

Patrícia Xufre – Substitute member (Assistant Professor)

Formal notification of results:

All candidates will be notified by email.

Application period:

The call is open from 31 of August to 15 of September 2021.

Application procedure:

Applications must be submitted by email to, under the subject Nova SBE/BIPD/2021/03, and must include the following documents (mandatory):

1.     Motivation letter;

2.     Detailed Curriculum Vitae;

3.     Transcripts of diplomas or degrees with final grades and other documents demonstrating the candidate’s suitability for the required profile;

4.     For degrees obtained abroad applicants must submit the recognition of the academic degree and the converted final grade to the Portuguese grading scale (following the Decree-Law no 341/2007 of 12 October), or the recognition of foreign qualifications (following the Decree-Law no. 283/83, of 21 June). Optional


In accordance with the article 12 of Regulamento de Bolsas de Investigação Científica of Nova SBE, the candidate can appeal from the decision with the Scientific Council of Nova SBE, Faculdade de Economia da UNL, within 10 working days.


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