Data Science Analyst - Modelling (Data Analytics & AI)

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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