Job Description

Position Overview
The Data Science Analyst analyses data through application of scientific methods and data-discovery tools. They integrate and prepare large and varied datasets, and models complex business problems. They discovers business insights and identify opportunities through the use of statistical, algorithmic, mining and visualisation techniques. They assist with architecting specialised database and computing environments, developing methodologies, performing analysis, summarising results and developing conclusions . They possess a combination of analytic, machine learning, data mining and statistical skills as well as experience with algorithms and coding.
They have a deep passion for analysing and resolving complex business problems. They display an intellectual curiosity about the business needs as well as the capability to engage with stakeholders to understand business issues.
Role & Responsibilities
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
• Apply programming abilities to build software to scrub, combine, and manage data from a variety of sources

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

Present insights

• Assist with the development of actionable recommendations
• Develop compelling, logically structured presentations including story-telling of research/analytics findings
• Guide stakeholders on how to act on findings

Additional Responsibilities:

• Research on latest technologies and applications in the healthcare space
• Perform literature reviews and identify innovative technologies with potential application and impact in the healthcare sector, focusing on the adaptation of language and multimodal models to healthcare-specific use-cases
• Identify pain-points and formulate problem statements relevant to healthcare use-cases where novel technologies can be applied and bring value
• Identify appropriate sources of data for technology testing
• Perform Proof-of-Concept (PoC) studies to demonstrate the feasibility of implementing such technologies and document outcomes rigorously
• Support the implementation of AI-related policies within Synapxe
• Help in publication strategy and writing/reviewing papers
• Search and identify the most adequate and impactful peer-reviewed journals for publication of studies or project conducted at Synapxe Data Analytics and AI team
• Contribute to draft, review, and edit manuscripts following rigorous scientific writing style and standards
• Contribute ideas to improve the quality and acceptance likelihood of manuscripts
• Liase with external vendors/stakeholders to establish successful collaborations
• Train and manage junior staff

Requirements

• PhD or Masters in a quantitative field such as Mathematics, Statistics, Information Technology, Physics, Engineering, Finance or equivalent
• Proficiency in python programming language for data processing and model development
• Experience with pytorch, tensorflow, and other deep learning frameworks for developing and implementing neural networks
• Hans-on experience with prompt engineering, retrieval augmented generation, and LLM fine-tuning methodologies
• Experience with toolkits and platforms to build and deploy end-to-end LLM pipelines and agentic systems
• Knowledge of LLM observability and evaluation platforms for AI applications
• Familiarity with tools for orchestrating and managing distributed training of LLMs across GPUs
• Experience with cloud-based platforms for building, deploying, and managing AI models
• Familiarity with git and github repositories
• Ability to browse and retrieve articles and information from journal sites and scientific literature libraries
• Scientific writing skills
• Understanding of manuscript submission, guides for authors, and publication process
• Experience with tools to create publication-quality figures
• Familiarity with reference managing tools is a plus
• Knowledge with hypothesis testing and statistical tests is a plus
• Knowledge on digital technologies and AI policies in the Government sector and experience with strategic planning and management in Healthcare institutions
• Ability to communicate effectively and present results and findings
• Ability to multitask and work as part of a multidisciplinary team
• Adaptability to work on a constantly evolving environment
• Ability to document work comprehensively and rigorously
• Knowledge on digital technologies and AI policies in the Government sector and experience with strategic planning and management in Healthcare institutions
• Ability to communicate effectively and present results and findings
• Ability to multitask and work as part of a multidisciplinary team
• Adaptability to work on a constantly evolving environment
• Ability to document work comprehensively and rigorously

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