Principal Data Scientist – Network Analytics

Principal Data Scientist – Network Analytics – Dublin & Letterkenny, Ireland

Optum is a global organisation that delivers care, aided by technology, to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data, and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits, and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. 

In healthcare, evolution does not just happen. It takes innovation, imagination, and a passion for solving problems in new and better ways. And innovation is taking place at a lightning-fast pace every day at Optum.  

As the fastest growing part of the UnitedHealth Group family of businesses, we’re expanding our team in Ireland and creating excellent opportunities for those who want greater purpose and more impact in their work. We’ll provide the investment, support, and resources to advance your career. You’ll provide the talent, ambition, and drive. 

As a Principal Data Scientist in the Network Analytics team you will play a pivotal role in shaping the future of healthcare by applying data science techniques to solve some of the most pressing challenges in the U.S. healthcare system. Join us and be part of a dynamic team that is making a real difference in the lives of millions. 

This is a full-time position with standard working hours of Monday – Friday, 9am – 5pm.

Careers with Optum offer flexible work arrangements and individuals who live and work in the Republic of Ireland will have the opportunity to split their monthly work hours between our Dublin or Letterkenny office and telecommuting from a home-based office in a hybrid work model. 

Primary Responsibilities: 

• Code daily to build and deploy impactful data science solutions, taking full ownership of projects from problem framing and data exploration to model development, deployment, and monitoring—delivering measurable improvements in healthcare cost, quality, and access
• Lead by example as a hands-on technical expert, writing production-grade code and contributing directly to the development of big data systems, pipelines, and tools
• Collaborate closely with business and technical leadership, acting as a strategic thought partner to shape the roadmap for data-driven innovation across provider networks, claims data, and member experience
• Design and implement scalable, real-world machine learning systems, balancing performance, interpretability, and operational constraints in high-stakes healthcare environments
• Drive cross-functional initiatives, using experimentation, and advanced analytics to define success metrics and guide decision-making
• Mentor and elevate the data science team, conducting code reviews, setting technical standards, and fostering a culture of curiosity, rigor, and continuous learning
• Translate complex healthcare data into actionable insights, integrating diverse data sources to build a comprehensive view of network behavior, risk, and opportunity
• Proactively surface emerging risks and opportunities, using anomaly detection, fraud analytics, and pattern recognition to inform strategic interventions
• Contribute to the evolution of data science infrastructure, working with platform teams to enhance tooling for experimentation, model monitoring, and reproducibility
• Represent the data science function in executive forums, clearly communicating technical insights and their strategic implications to influence decisions and investments
• Develop your understanding of healthcare and the U.S. healthcare system, ensuring that solutions are context-aware and impactful

You will be rewarded and recognised for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role, as well as providing development for other roles you may be interested in.

Required Qualifications: 

• Bachelor’s Degree in a quantitative field such as mathematics, statistics, computer science, actuarial science, engineering, or related discipline
• Extensive experience in SQL and Python/R with a strong track record of building data science solutions
• Demonstrated ability to solve complex technical problems through hands-on coding and model development
• Experience applying data science to real-world business challenges, driving measurable impact

Preferred Qualifications: 

• Master’s Degree, PhD in a quantitative field or relevant professional qualification

Soft Skills:

• Strong communication skills, with the ability to explain technical concepts to diverse audiences and influence decision-making

• Leadership in collaborative, cross-functional settings, including mentoring and setting technical direction

 

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone–of every race, gender, sexuality, age, location and income–deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalised groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

 

Diversity creates a healthier atmosphere: Optum is an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to gender, civil status, family status, sexual orientation, disability, religion, age, race, and membership of the Traveller community, or any other characteristic protected by law. Optum is a drug-free workplace. © 2025 Optum Services (Ireland) Limited. All rights reserved.

 

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