eHealth Africa is focused on improving healthcare by creating effective ways to implement reliable health information management systems. We have developed eHealth and mHealth solutions that can be rapidly deployed to manage patient information, streamline clinical procedures, and provide data and analysis on health program outcomes. Accurate health data will provide NGO’s, hospitals, and donor agencies with access to timely health system indicators needed to evaluate their health interventions and respond to critical public health needs. We bring about positive change by harnessing the potential of technology, valuing the power and knowledge of local people, and maintaining a sharp focus on the health worker. To help close the gap in access to health care we have developed and share a depth of expertise in: eHealth and mHealth software and solutions Technology Infrastructure Training and capacity building for sustainable health systems Research and data analysis Project Management eHealth Africa works closely with health NGOs in order to provide them with technology solutions that will enhance their on-going and new health programs. We also strive to work with state and government officials to manage large scale implementations at health facilities across the country. eHealth and Information Systems Africa, Inc. is a California, USA Public Service Corporation. We have offices based in California, USA, and Kano, Nigeria.
- Job Type: Full Time
- Qualification: BA/BSc/HND
- Experience: 4 years
- Location: Abuja , Kano
- Job Field: ICT / Computer , NGO/Non-ProfitÂ
Purpose of the position
- We are seeking a highly skilled and motivated AI and Machine Learning Expert with expertise in disease modeling to join our dynamic team.
- The ideal candidate will play a key role in developing advanced algorithms and models that enable the accurate prediction, monitoring, and control of infectious diseases.
- This position offers an exciting opportunity to contribute to cutting-edge projects and innovation in the field of public health.
Keywords:
Artificial Intelligence (AI), Machine Learning (ML), Disease Modeling, Predictive Analytics, TensorFlow
What you’ll do
- Develop and implement state-of-the-art machine learning algorithms and techniques for disease modeling and prediction, with a focus on infectious diseases such as cholera, malaria, tuberculosis, HIV/AIDS, emerging infectious diseases.Â
- Design and optimize predictive models using large-scale datasets, including epidemiological data, genomic data, environmental data, and clinical data.
- Collaborate with cross-functional teams to understand business requirements and identify opportunities for leveraging machine learning and AI.
- Conduct in-depth analysis of large and complex datasets to extract actionable insights and trends.
- Evaluate the performance of machine learning models, iterate on model designs, and optimize for scalability and efficiency.
- Collaborate with epidemiologists, biostatisticians, data scientists, and software engineers to integrate machine learning solutions into user-friendly software platforms and tools.
- Conduct rigorous evaluation and validation of machine learning models using appropriate metrics and methodologies, ensuring robust performance across diverse populations and geographic regions.
- Stay abreast of the latest advancements in AI, ML, and disease modeling research, and proactively identify opportunities for innovation and improvement.
- Communicate research findings, insights, and technical concepts effectively to both technical and non-technical stakeholders through presentations, reports, and scientific publications.
- Provide technical guidance and mentorship to junior team members, fostering a collaborative and innovative work environment.
- Experience with DevOps practices and tools such as Git, Jenkins, and Travis CI.
- Researches, and evaluates data solutions and libraries, providing recommendations on new technology relevant to exploration and growth.
Data Management
- SharePoint, Data Analytics, SNL and other mining and markets third party data sources
Generator of Geospatial Knowledge and Analytics. - Continuous improvement, keep abreast and apply new technologies that are fit for purpose within the machine learning and Analytics fields.
- Linking data warehouse (SQL) to various applications and analytics sites. Maintaining and updating of key GIS datasets, participate and become a key contributor to the way forward for enterprise wide GIS systems.
- Owning Data Warehouse for Exploration and Growth.
- Staff meetings, training classes and supervision.
- Adheres to Policies and Procedures.
- Adheres to eHealth Africa Code of Conduct as well as ethical standards of the field.
Who you are
The requirements listed below are representative of the knowledge, skill and/or ability required to successfully perform this job.
- Master’s degree in Computer science, statistics, bioinformatics, epidemiology, or a related field with a strong emphasis on machine learning and data science. A postgraduate Degree will be an added advantage
- Minimum of 4 years work experience and proven track record of research and publication in the fields of Artificial Intelligence, Machine Learning, and disease modeling, with a focus on infectious diseases preferred.
- Proficiency in programming languages such as Python, R, or Julia, and experience with popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Deep understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, ensemble methods, and time series analysis.
- Experience working with large-scale healthcare datasets, epidemiological data, genomic data, and geospatial data is highly desirable.
- Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights and solutions.
- Excellent communication and interpersonal skills, with the ability to collaborate effectively in interdisciplinary teams and communicate technical concepts to diverse audiences.
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.