Intermediate Data Scientist – Health Operations Intelligence

About the role

Discovery Health is looking for an Intermediate Data Scientist to join its Operations Intelligence unit. You will use large clinical, demographic and operational datasets to build predictive models and machine‑learning solutions that improve service delivery and create delightful experiences for members.

Key responsibilities

• Engage with a wide range of stakeholders to translate healthcare and operational questions into data‑driven projects.
• Mine and analyse structured and unstructured data to uncover insights that boost operational efficiency and member satisfaction.
• Research, develop and apply state‑of‑the‑art machine‑learning and AI algorithms, including large language models and generative AI.
• Collaborate with product owners, project managers and senior leaders to prioritise business problems suitable for AI solutions.
• Conduct desktop research on the latest LLM and generative AI advancements and propose practical applications.
• Present model results and data visualisations in clear, actionable formats for business users.
• Monitor model performance over time and refine as needed.
• Identify and implement improvements to data pipelines, databases and analytical processes.

Required profile

• Strong expertise in data‑science programming languages such as R, Python and Scala.
• Advanced SQL skills for data extraction, transformation and loading.
• Proven experience in interactive data exploration and storytelling with data.
• Solid understanding of big‑data concepts and distributed computing principles.
• Hands‑on experience with big‑data platforms (e.g., Hadoop, Spark) is preferred.
• Deep analytical and statistical knowledge, including modern machine‑learning techniques for both structured and unstructured data.

Required skills

• R
• Python
• Scala
• SQL
• Big Data systems (e.g., Hadoop, Spark)

What we offer

• Opportunity to work on high‑impact health‑care analytics projects.
• Access to cutting‑edge data‑science tools and large‑scale data sets.
• Collaborative environment with global thought leaders.