• Application Deadline:
• Position: Machine Learning, Data Coordinator


• Job Type Full Time


• Qualification BA/BSc/HND


• Experience 4 years


• Location Abuja , Kano


• Job Field Data, Business Analysis and AI  , NGO/Non-Profit  , Project Management 
  

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.