About the role

The role involves developing predictive and prescriptive analytics to optimize provider performance and care delivery within the healthcare domain. It also requires collaborating with cross-functional teams to build scalable data products and implement responsible AI practices.

What they look for

Python SQL NoSQL AWS Databricks Generative AI Prompt Engineering RAG ICD Data Analysis Predictive Analytics Prescriptive Analytics Data Governance EU AI Act Agile Methodology Communication

Requirements

Candidates need a degree in Data Science, Statistics, or a related field with practical experience in Python, SQL, and cloud platforms like AWS. Knowledge of ICD codes and foundational understanding of Foundation Models and the EU AI Act are also required.

Full description

The job profile for this position is Data Science Analyst, which is a Band 2 Senior Contributor Career Track Role.

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Data Science Analyst

Job Objective

We are seeking a data-driven and analytically minded professional to join the Data Science and AI Engineering team within International Health, Cigna Healthcare. Our team designs and delivers high-impact descriptive, predictive, and emerging AI-enabled analytics to address complex challenges across global and local healthcare markets.

This role is primarily aligned to the Provider domain, supporting insights related to healthcare providers such as hospitals, physician groups, and ancillary care organizations, and their interaction with health insurance operations. The position will also collaborate closely with adjacent domains, like Clinical and Payment Integrity, to ensure analytics are grounded in clinical relevance, operational efficiency, and value-based care outcomes.

This is an opportunity for a data analyst to demonstrate strong technical capability and business acumen by translating data into actionable insights and scalable data products that drive measurable value for healthcare and health insurance stakeholders.

Job Responsibilities

Work with Product Owners and domain stakeholders to understand provider-related business questions and contribute to the selection of appropriate analytical approaches
Assist in the development and implementation of predictive and prescriptive analytics, supporting use cases such as provider performance analysis, network insights, and care delivery optimization
Participate in an agile operating model, contributing to sprint activities, backlog items, and iterative delivery of analytics and data products within cross-functional teams
Support the use of generative AI–enabled analytics in a controlled and responsible manner, including contributing to knowledge bases that enable Retrieval‑Augmented Generation (RAG) for analytics and insight discovery
Contribute to the creation and maintenance of quality provider datasets by helping identify critical data elements (CDEs) and supporting data quality, consistency, and usability for analytics
Assist in tracking and communicating the business value and outcomes associated with analytics and data products
Collaborate with Data Engineering and Cloud Engineering teams to support data ingestion, enrichment, and availability across first- and third-party healthcare and provider data sources
Work with Data Governance and AI Governance teams to follow data protection, responsible AI practices, and EU AI Act–related requirements, building familiarity through practical application

Requirements

Tertiary education in Data Science, Statistics, Computer Science, Engineering, or a related discipline
Working knowledge of International Classification of Diseases (ICD) and its use in healthcare and health insurance analytics
Practical experience using Python for data analysis
Experience querying and working with SQL and NoSQL data stores
Exposure to cloud-based data and analytics platforms, preferably AWS and Databricks (e.g., SageMaker, Athena, or equivalent tools)
Basic to intermediate understanding of Foundation Models, including common use cases and limitations in enterprise settings
Some hands-on exposure to prompt engineering or agent-based approaches, supporting analytics or insight-generation workflows
Awareness and foundational knowledge of the EU AI Act, with interest or initial experience applying governance, transparency, or risk-related concepts in analytics or AI initiatives
Good communication skills in English, with the ability to explain analytical findings clearly to non-technical stakeholders; additional languages are an advantage

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