Machine Learning, Data Coordinator

2 months ago

Abuja Kano, Nigeria eHealth Systems Africa 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.

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