SNKE: Expert in Advanced Statistical Analysis Method in OHS

Job Description

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 is to strengthen 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.

Activity title: Intervention 5.5: Training on Advanced Statistical Analysis Method for Health Physical and Social Sciences in OHS

Objectives:

The particular focus of this training will be on building on the trainings delivered in Intervention 5.4 (in addition to those in Interventions 5.2 and 5.3). During this training intervention the participants are introduced:

• To learn the ‘Analysis of Variance’ (ANOVA) and ‘Analysis of Covariance’ (ANCOVA), the regressions techniques (multiple logistics, multiple linear, poison and cox regressions), and multivariable modelling.
• To consider how each individual statistical test works, for what data and design in it is appropriate, and how the results should be interpreted. Participants will also learn how to perform these techniques by using Python programming.
• To understand how to use regression analyses (linear and exponential) and multiple regression (linear and logistic), one-way and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test, runs test).
• To understand why regression models, a subset of linear models, are the most important statistical analysis tools in a data scientist’s toolkit.
• To understand and use regression analysis, least squares, inference using regression models, and analysis of residuals and variability. The course will cover modern thinking on model selection and novel uses of regression models, including scatterplot smoothing.
• To study and examine during the final 2-day research project, in groups of five, a research hypothesis and design, create manipulation and measurement instruments, collect data, perform advanced statistical analyses and document the results.

Brief description of the assignment :

Working with Key Expert 2, the Team Leader and the Beneficiary in accordance with the tasks and duties set out below, the SNKE: Expert in Advanced Statistical Analysis Method in OHS - will be responsible for the 7-day session of Intervention 5.5: Training on Advanced Statistical Analysis Method for Health Physical and Social Sciences in OHS for all three sessions:

• Finalising the training programme by reviewing the indicative programme in Table 1, and revising it if needed.

• Preparing and using his/her training materials according to the final training programme.
• Teaching advanced statistical methodologies and regression methods for OHS in detail to the participants (simultaneous translation is provided if needed).
• Preparing the trainer assessment part which includes the used training materials to the training assessment report.

She/he will work under the direct supervision of KE2 and the overall supervision of the Team Leader (KE1).

Training programme:

Day 1: Introduction to the regression: Linear and Logistic Regression with Python

Day 2: Analysis of variance and covariance model with data examples

Day 3: Multivariable Analysis

Day 4: Regularization for overtraining

Day 5: Imbalance Learning

Day 6: Final Project

Day 7: Final Project

Dinner organisation

Expected deliverables:

The Expert in Advanced Statistical Analysis Method in OHS is responsible for:

• Finalizing the updated training course programme and training materials,
• Keeping training records on course for participants’ attendance,
• Distributing and collecting of training pre-post test questionnaires at the beginning and end of the training, and
• Final report (Trainer assessment part in training assessment report).

Commencement date of the project: February 2022

Duration of the assignment: 26 workdays over 5 months

Requirements

Qualifications and skills:

• Bachelor’s degree or higher degree in one of the fields of engineering or statistics, OHS, biostatistics or in the absence of such a degree, at least 10 years of working experience in the field of research and/or statistics.
• Good command of written and spoken Turkish or English.
• Good computer literacy.
• Good command of written and spoken English would be an asset.
• A Master’s degree or higher degree on statistics would be an asset.

General professional experience:

• At least 8 years of professional experience in OHS or statistics training, education or OHS-related activities.
• Personal communication and reporting skills.
• Ability to work in a team.

Specific professional experience:

• Experience in statistical applications in Python programming.
• Experienced in EU project, writing instructions and reports will be an asset.

About the Organization

DAI is the largest single provider of development services to the European Commission.

From corporate locations in Ankara (Turkey), Belgrade (Serbia), Brussels (Belgium), Cologne (Germany), London (United Kingdom), Sofia (Bulgaria), and Vienna (Austria), our team of 100+ employees oversees a portfolio of more than 95 EU projects in more than 80 countries.

Our EU Business Unit covers the whole spectrum of DAI operations, from project delivery, framework contract implementation, and global facilities management to business development, communications, and knowledge management. The EU team is seamlessly integrated into DAI’s global organisation, tapping the full range of technical specialists and support staff from our United States, United Kingdom, Nigeria, Pakistan, Palestine, and other locations.

This team orchestrates a network of some 800 in-house and external experts currently engaged on short- and long-term assignments encompassing all EU technical areas, including governance and public administration reforms, sustainable economic growth and agriculture, resilience, conflict and security, gender and social inclusion, climate change and green growth, digitalisation, global health, education, and social protection.

DAI has extensive experience working with the Directorate-General for International Partnerships (DG INTPA), Directorate-General for Neighbourhood and Enlargement Negotiations (DG NEAR), the EU’s External Action Service (EEAS), and European development financial institutions such as the European Bank for Reconstruction and Development (EBRD) and the European Investment Bank (EIB).

We partner with these and other clients to support the European Consensus on Development and achieve the United Nations Sustainable Development Goals. As a signatory of the UN Global Compact, we report on our contributions to achieving the SDGs in our annual Communication on Progress. In 2021, we signed up to the Science-Based Targets Initiative (SBTI) for greenhouse gas emission reductions. As an employee-owned and mission-oriented enterprise, we are wholly committed to upholding the highest standard of responsible and sustainable business.”

As an employee-owned and mission-oriented enterprise, we are wholly committed to upholding the highest standard of responsible and sustainable business.