Data Scientist Senior Analyst - Cigna Healthcare
Cigna
- Location
- Madrid, Spain
- Work model
- On-Site
- Level
- Senior
- Posted
- Sep 8, 2026
Skills
About this role
About Cigna Healthcare Cigna Healthcare is a global health service company dedicated to transforming healthcare. With roots in the U.S. and operations in over 30 countries, we serve more than 180 million customers and patients worldwide. Ranked 13th on the Fortune 500 in 2025, Cigna is recognized as one of the most trusted and influential names in the industry. Our mission is to improve the health, well-being, and peace of mind of those we serve. You’ll join a globally recognized organization where trust, clear communication, and a positive culture shape how we work. Our leaders are consistent, approachable, and supportive, helping you maintain balance while doing meaningful work. We look for people who thrive in collaborative environments, care about meaningful change, and want to grow in a company that puts people first. At Cigna Healthcare, your work contributes to better care experiences and supports customers through important moments in their lives.
About the Role
You will join the Data Science and AI Engineering team within International Health, where you will help translate complex healthcare and health insurance data into actionable insights and scalable analytics solutions. Your work will support business decision-making, provider-related strategies, and the responsible adoption of AI-enabled analytics across global and local healthcare markets. What You’ll Do Partner with Product Owners and business stakeholders to understand healthcare and provider-related challenges and recommend appropriate analytical approaches. Support the design and implementation of predictive and prescriptive analytics that inform provider engagement strategies, network optimization, and care delivery outcomes. Contribute to the delivery of analytics and data products within an agile environment, working closely with cross-functional teams through iterative delivery cycles. Support the responsible use of generative AI-enabled analytics, including the development and maintenance of domain-aligned knowledge bases for Retrieval-Augmented Generation (RAG), agent-assisted analytics, and insight generation use cases. Design, curate, and maintain provider datasets, ensuring data quality, completeness, consistency, and suitability for advanced analytics and AI-driven solutions. Measure and communicate the business impact and value generated through analytics and AI-enabled data products. Collaborate with Data Engineering, Cloud Engineering, Data Governance, and AI Governance teams to support data availability, regulatory compliance, and responsible AI practices. What You’ll Bring Tertiary education in Data Science, Statistics, Computer Science, Engineering, or a related discipline. Knowledge of International Classification of Diseases (ICD) and its application within healthcare and health insurance analytics. Hands-on experience using Python for data analysis and modeling. Experience working with SQL and NoSQL databases. Experience with cloud-based data and analytics platforms, preferably AWS and Databricks. Strong English communication skills with the ability to translate analytical findings into clear, business-relevant insights.
Skills
Soft Skills Strong communication and stakeholder engagement skills. Ability to translate technical concepts into clear business narratives. Collaborative approach to working within cross-functional teams. Ability to communicate the value and impact of analytics solutions to different audiences. Technical / Functional Skills Python for data analysis and modeling. SQL and NoSQL databases. Cloud-based analytics and data platforms. AWS services such as SageMaker, Athena, or equivalent technologies. Databricks. Predictive and prescriptive analytics. Knowledge of ICD and healthcare analytics. Understanding of Foundation Models, including capabilities, limitations, risks, and enterprise usage considerations. Experience with prompt engineering and agent engineering supporting analytics workflows, RAG-based