SNKE - Data Scientist

Project title: Technical Assistance for Strengthening Training and Research Capacity of the Centre for Labour and Social Training and Research (ÇASGEM)

Brief description of the project: The purpose of this three-year EU Technical Assistance Project for “Strengthening Training and Research Capacity of the Centre for Labour and Social Training and Research (ÇASGEM)” is to strengthen the institutional capacities of ÇASGEM, relevant stakeholders, social partners and NGOs through adapting training modules in occupational rehabilitation; delivering trainings for trainers; designing virtual training scenarios; carrying out awareness-raising activities; conducting researches; and organizing study visits, workshops and seminars in the field of occupational health and safety, especially in construction, mining, chemical and metal sectors.

Intervention 9: Research on Return-to-Work Programme (RTW)

Position: SNKE - Data Scientist

Resources: Up to 28 Working Days

Working Period: Jun 2022 – Oct 2022

Tasks:

• Literature review.
• Active involvement in data acquisition, mining and cleaning, and analysis processes.
• Participating in the technical meetings with the relevant institutions for data acquisition and collaboration.
• Participating in the working group meetings to discuss the plans and progress.
• Comparative analysis and evaluation of potential models and/or algorithms for implementation of Return to Work (RTW) programmes.
• Preparing the final report presenting results from the research.

Required Qualifications:

• At least 10 years of professional experience.
• Post graduate degree in Statistics, Computer Science or related fields.
• Excellent written and verbal language skills in English and Turkish.
• Excellent knowledge of Python programming language and its libraries.
• Good writing and reporting skills.
• Capable of programming models and/or algorithms.

Following Qualifications would be an advantage:

• At least 5 years of experience in data mining and data analysis.
• PhD in Statistics, Computer Science or related fields.
• Prior experience in working with SSI and its databases.
• Prior experience in working with labour statistics.