Overview

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.

Job Position: Machine Learning, Data Coordinator

Job Locations: Abuja (FCT) and Kano

Job Description

  1. We are seeking a highly skilled and motivated AI and Machine Learning Expert with expertise in disease modeling to join our dynamic team.
  2. 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.
  3. 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

Job Responsibilities

  1. 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.
  2. Design and optimize predictive models using large-scale datasets, including epidemiological data, genomic data, environmental data, and clinical data.
  3. Collaborate with cross-functional teams to understand business requirements and identify opportunities for leveraging machine learning and AI.
  4. Conduct in-depth analysis of large and complex datasets to extract actionable insights and trends.
  5. Evaluate the performance of machine learning models, iterate on model designs, and optimize for scalability and efficiency.
  6. Collaborate with epidemiologists, biostatisticians, data scientists, and software engineers to integrate machine learning solutions into user-friendly software platforms and tools.
  7. Conduct rigorous evaluation and validation of machine learning models using appropriate metrics and methodologies, ensuring robust performance across diverse populations and geographic regions.
  8. Stay abreast of the latest advancements in AI, ML, and disease modeling research, and proactively identify opportunities for innovation and improvement.
  9. Communicate research findings, insights, and technical concepts effectively to both technical and non-technical stakeholders through presentations, reports, and scientific publications.
  10. Provide technical guidance and mentorship to junior team members, fostering a collaborative and innovative work environment.
  11. Experience with DevOps practices and tools such as Git, Jenkins, and Travis CI.
  12. Researches, and evaluates data solutions and libraries, providing recommendations on new technology relevant to exploration and growth.

Data Management:

  1. SharePoint, Data Analytics, SNL and other mining and markets third party data sources
    Generator of Geospatial Knowledge and Analytics.
  2. Continuous improvement, keep abreast and apply new technologies that are fit for purpose within the machine learning and Analytics fields.
  3. 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.
  4. Owning Data Warehouse for Exploration and Growth.
  5. Staff meetings, training classes and supervision.
  6. Adheres to Policies and Procedures.
  7. Adheres to eHealth Africa Code of Conduct as well as ethical standards of the field.

Job Requirements
The requirements listed below are representative of the knowledge, skill and/or ability required to successfully perform this job:

  1. 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
  2. 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.
  3. Proficiency in programming languages such as Python, R, or Julia, and experience with popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  4. Deep understanding of machine learning algorithms, including supervised and unsupervised learning, deep learning, ensemble methods, and time series analysis.
  5. Experience working with large-scale healthcare datasets, epidemiological data, genomic data, and geospatial data is highly desirable.
  6. Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights and solutions.
  7. Excellent communication and interpersonal skills, with the ability to collaborate effectively in interdisciplinary teams and communicate technical concepts to diverse audiences.
  8. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.

Application Deadline
12th August, 2024.

How to Apply
Interested and qualified candidates should:
Click here to apply online

Tagged as: Data, Information Technology

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