Assistant Researcher I – Statistics and Data Science

🎯 Senior 🎓 Bachelor Required

Job Title: Assistant Researcher I – Statistics and Data Science

 The Armauer Hansen Research Institute (AHRI) was founded in 1970 through the initiative of the Norwegian and Swedish Save the Children organizations seconded by the Ministry of Health of Ethiopia. The Institute got its name from the Norwegian physician, Gerhard Henrik Armauer Hansen, who first described the leprosy bacillus (Mycobacterium leprae). AHRI is a biomedical research institute that works in developing tools for prevention, control and treatment of mycobacterium and other diseases of public health importance through applied and basic biomedical research and training.

 The Malaria and Neglected Tropical Diseases Research (MNTD) Division of AHRI has secured different grants on malaria that have qualitative study work packages. These studies will be implemented in different selected study sites throughout the country. Therefore, the MNTD Division is looking for self-driven, motivated, innovative, and energetic Assistant Researcher I – Statistics and Data Science   who can coordinate the different malaria projects and perform tasks related to formative research.

  Description of Roles and Responsibilities

The successful candidate will join the study team and work closely with the project team members. The Assistant Researcher I is expected to perform the following tasks.

 Duties and Responsibilities

1. Statistical analysis

• Conduct descriptive and inferential analyses of malaria data from cross-sectional studies, cohorts, clinical or therapeutic-efficacy studies, surveillance systems, laboratory investigations, entomological studies and programme datasets.

• Apply appropriate statistical methods, which may include generalized linear models, logistic and count regression, mixed-effects models, longitudinal analysis, survival analysis, diagnostic-accuracy analysis, time-series analysis, under supervision.

• Apply data-science and machine-learning approaches when scientifically justified, including prediction, classification, clustering, feature engineering, model validation and performance assessment.

• Prepare clear tables, figures, dashboards and other visual summaries for technical and non-technical audiences.

• Assess model assumptions, missing data, bias, confounding, uncertainty, sensitivity and robustness; document analytical decisions and limitations.

1. Data management, programming and reproducibility

• Clean, validate, merge, reshape and analyse complex datasets while preserving original data and maintaining traceable data-processing workflows.

• Develop and maintain data dictionaries, analysis-ready datasets, quality-control checks, metadata, codebooks and versioned analytical scripts.

• Use reproducible programming practices in R and/or Python; use Stata, Git or other relevant tools as required by the project.

• Support the development of databases, electronic data-capture systems and automated data pipelines

• Maintain data security, confidentiality, access control, file organisation, regular backups and compliance with approved protocols and data-governance procedures.

1.  Study design and research support

• Contribute to protocol development, study design, sampling strategies, sample-size calculations, randomisation procedures and statistical analysis plans.

• Review data-collection tools and study databases to ensure that variables, coding, skip patterns and validation rules meet analytical requirements.

• Support data-quality monitoring during fieldwork and laboratory work, identify inconsistencies early, and work with project teams to resolve them.

• Conduct focused literature reviews on statistical, epidemiological and data-science methods

• Assist senior researchers in selecting appropriate analytical methods and interpreting findings in their biological, epidemiological and programme context.

1. Reporting, scientific writing and communication

• Prepare statistical sections of research protocols, reports, conference abstracts, presentations, manuscripts, policy briefs and funding proposals.

• Generate publication-quality tables and figures and ensure consistency between analytical outputs, manuscripts and supplementary materials.

• Contribute to scientific manuscripts and respond to statistical or data-related comments from co-authors, reviewers and partners under supervision.

• Present analytical progress and findings during project meetings, seminars, journal clubs and national or international scientific meetings.

• Communicate analytical findings clearly to researchers from clinical, laboratory, entomological, epidemiological and public-health backgrounds.

1.  Collaboration and capacity development

• Work effectively with statisticians, data scientists, epidemiologists, clinicians, laboratory scientists, entomologists, field teams and programme stakeholders.

• Provide routine analytical support to assigned malaria projects and manage agreed tasks, timelines and deliverables.

• Share code, documentation and analytical lessons with the Statistics/Data Science team and contribute to internal peer review.

• Perform other related duties assigned by the Principal Investigator or Statistics Team Lead.

Job Requirements

Required Education and Qualifications

• BSc in Statistics, Data Science with strong quantitative training, or another closely related field. At least two years of relevant work experience in statistical analysis, data science, health research, surveillance, research data management and a comparable quantitative role.

• Minimum CGPA of 3.00 for male and 2.75 for female applicants.

 Technical Skills and Experience

• Strong foundation in statistical reasoning, epidemiological concepts, study design and interpretation of quantitative research findings.

• Practical proficiency in R is strongly preferred; proficiency in Python and/or Stata is also highly desirable.

• Ability to write, debug and document analytical code and to produce reproducible results from raw data to final tables and figures.

• Experience with data cleaning, reshaping, merging, validation, missing-data assessment and preparation of analysis-ready datasets.

• Experience with common statistical methods, including regression modelling and at least one of the following: longitudinal, survival, mixed-effects, time-series, Bayesian analysis.

• Ability to produce high-quality statistical tables, data visualisations and written summaries.

• Working knowledge of spreadsheet tools and database concepts

• Ability to read scientific literature, understand research protocols and explain statistical findings to multidisciplinary teams.

• Strong written and spoken English; ability to prepare clear technical documentation and presentations.

Employment Details

• Duty station: Addis Ababa

• Number required: 1 (one)

• Salary: ETB: As per the institution scale

• Terms of employment: One-year contract period on a full-time employment basis with possibility of extension

How To Apply

Interested applicants who fulfil the above requirements should send the following through EthioJobs:

• A CV/resume (not more than 4 pages)

• A cover letter (not more than one page)

• A one-page table summarizing your educational background, technical skills, and competencies to facilitate the screening process

Apply