Senior Data Analyst

Requirements:

• At least 8 - 10 years’ experience in developing, implementing and maintaining IT systems
• Solid experience in applying AI and machine learning techniques to medical imaging or healthcare datasets.
• Proficiency 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.

Role and Responsibilities:

The Data Science Analyst analyses data through application of scientific methods and data-discovery tools. He integrates and prepares large and varied datasets, and models complex business problems. He/She discovers business insights and identifies opportunities through the use of statistical, algorithmic, mining and visualisation techniques. He assists with architecting specialised database and computing environments, developing methodologies, performing analysis, summarising results and developing conclusions . He possesses a combination of analytic, machine learning, data mining and statistical skills as well as experience with algorithms and coding.

He has a deep passion for analysing and resolving complex business problems. He displays an intellectual curiosity about the business needs as well as the capability to engage with stakeholders to understand business issues.

Manage projects:

• 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

Prepare data sets:

• Drive data collection efforts

• Assist with developing new data-discovery tools

• Extract data from data sources

• Propose new uses for existing data sources and structures

• Integrate multiple data sets to build large and complex data sets

Analyse data:

• 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

• Implement automated processes for efficiently producing scale models

• Identify areas of improvement of current processes, products/services or analytical models

• Apply programming abilities to build software to scrub, combine, and manage data from a variety of sources