| Position Title: | Data Scientist – AMR Epidemiologist (Mapping Antimicrobial Resistance and Antimicrobial Use Partnership (MAAP) Consortium) |
| Nature of the Position: | Regular/Full time |
| Reports to: | Portfolio Lead |
ASLM background
The African Society for Laboratory Medicine (ASLM) is a pan-African professional body working to advocate for the critical role and needs of laboratory medicine and networks throughout Africa. Africa is rapidly growing but faces major health challenges including epidemics of HIV, tuberculosis, and malaria, and new priorities such as Ebola and other global health security threats. Strengthened laboratory capacity and surveillance in Africa are critical to overcoming the burden of disease and ensuring a healthy future for the continent. ASLM addresses these challenges by working collaboratively with governments, local and international organizations, implementing partners, and the private sector.
Project Background
Mapping Antimicrobial Resistance and Antimicrobial Use Partnership (MAAP) is a multi-organization and multi-national consortium led by ASLM and funded by the UK Government’s Fleming Fund and managed by Mott McDonald. MAAP focuses on improving the quality and quantity of Antimicrobial Resistance (AMR) data, analysis, and dissemination. In Phase I, MAAP collected AMR/AMC data from 2016 to 2019 across 14 African countries. The results, including analysis, gaps, and opportunities, along with policy recommendations, are summarized in a policy brief available on ASLM’s website. The project Phase II aims to address data gaps and enhance quality for future initiatives, strengthening surveillance capacity to inform regional and national efforts in improving AMR surveillance, antimicrobial stewardship, and evidence-based policy and planning.
Job Overview
We are seeking a highly skilled and motivated Data Scientist to join our team dedicated to combating Antimicrobial Resistance (AMR), a significant threat to global public health. This pivotal role in our AMR team involves providing leadership for the analysis of antimicrobial resistance (AMR) and Antimicrobial Use (AMU), utilizing advanced technologies to manage, analyze, and interpret scientific data effectively. The incumbent will guide AU member countries with strategies in addressing this critical issue.
Key Responsibilities:
- Data Collection and Cleaning: Guide the project team and countries to gather, curate, and clean various datasets related to AMR and AMU, including laboratory and pharmacy data, clinical records, and epidemiological data.
- Data Analysis: Perform exploratory data analysis, using statistical methods to identify patterns, trends, and insights related to AMR and AMU data.
- AMU Data Analysis: Lead and support AMU data analysis to reveal antimicrobial consumption patterns across countries.
- Data Visualization: Use mapping tools to create informative and visually appealing visualizations of AMR and AMU datasets, communicating findings to both technical and non-technical stakeholders.
- Collaboration: Work closely with cross-functional teams, integrating data-driven insights into AMR mitigation strategies, and collaborating with other advisors to align lab informatics strategies.
- Research and Innovation: Stay updated with the latest advancements in data science, machine learning, and AMR research to bring cutting-edge approaches to projects.
- Reporting: Assist countries in generating clear reports and presentations summarizing findings, methodologies, and recommendations for internal and external audiences, contributing to policy implications resulting from the data.
- Data Security and Ethics: Ensure data privacy and security compliance, adhering to ethical guidelines when handling sensitive healthcare data.
Qualifications and Skills:
- Bachelor’s or advanced degree in Epidemiology, Public Health, Information Systems, Data Science, Computer Science, Statistics, or a related field.
- Master’s level or above is an advantage.
- Proven experience in data analysis and predictive modeling, with a focus on healthcare or biology-related datasets.
- Practical experience in driving digital transformation and modernizing lab informatics.
- Proficiency in programming languages such as Python and R, along with experience in data analysis libraries and frameworks.
- Knowledge of AMR, microbiology, and healthcare data is a strong plus.
- Excellent communication and collaboration skills to work effectively with a multidisciplinary team.
- Strong problem-solving skills and a proactive, innovative mindset.
- Knowledge of data security and ethical considerations in data science.
- Stay updated on emerging technologies, such as AI-driven somatic search and intelligent instruments.
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