Responsibilities:
- Analyses data through the application of scientific methods and data-discovery tools.
- Integrates and prepares large and varied datasets, and models.
- Discovers business insights and identifies opportunities through the use of statistical, algorithmic, mining and visualisation techniques.
- Assists with architecting specialized database and computing environments, developing methodologies, performing analysis, summarising results and developing conclusions,
- Assists in the conceptualization of analytical projects
- Maintain project plans and status reports for all incoming and active projects
- Provide subject matter expertise to stakeholders throughout the whole analytics lifecycle
- Prepare documentation to outline data sources, models, and algorithms used and developed
- Apply data mining techniques and programming skills to investigate leads, identify patterns and regularities in data
- Develop data models based on advanced statistical modelling, data mining, and machine learning methods
- Identify areas of improvement of current processes, products/services or analytical models Present insights
- Assist with the development of actionable recommendations.
Requirements:
- Master’s or Bachelor’s in Computer Science, Mathematics, Statistics, Information Technology, Physics, Engineering or equivalent, with a strong focus on computer vision/ deep learning.
- Experience in applying AI and machine learning techniques to medical imaging or healthcare datasets.
- Proficient in programming (Python etc.) and good experience with deep learning frameworks (TensorFlow, PyTorch etc).
- Hands-on experience in the development of image classification, object detection, segmentation, video analytics, multimodal model or related.
- Model deployment experience is preferred.
- Preferably 3 years of relevant working experience.
- Proven communication skill to explain insights from technical work to non-technical audiences through presentation or other means
- Ability to work independently.
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