eHealth Africa designs and implements data-driven solutions and technologies to improve health systems for and with local communities. eHA’s technology works in low connectivity settings and uses data to drive decision-making by local governments and partner agencies to get optimum results.
We are recruiting to fill the position below:
Job Title: Machine Learning, Data Coordinator
Locations: Abuja (FCT) and Kano
Employment Type: Full Time
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.
- 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.
Application Closing Date
Not Specified.
How to Apply
Interested and qualified candidates should:
Click here to apply online