Senior Data Scientist

Optum is a global organization 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.

Primary Responsibilities:

• Statistical Analysis and Modeling:
  
  
  • Conduct statistical methodologies such as regression analysis, propensity score matching, survival analysis, and generalized linear models
  • Apply advanced statistical techniques to analyze healthcare datasets for clinical and economic outcomes
• Data Management and Manipulation:

• Handle large, complex healthcare datasets (EHR, claims data, etc.)
• Operate data cleaning, data wrangling, and manipulation using tools like SQL, Python, R, or SAS

Programming and Technical Skills:

• Use programming languages like Python, R, or SAS for data analysis and statistical modeling
• Use tools like SQL for querying databases
• Create understanding of healthcare databases (claims, EHR, registry data, etc.) and their structure

Machine Learning and Predictive Analytics:

• Apply machine learning models to predict health outcomes, resource utilization, and treatment patterns
• Implement supervised and unsupervised learning algorithms, particularly in healthcare applications

HEOR & RWE knowledge:

• Real-world evidence generation, including health economics modeling, burden of illness studies, and comparative effectiveness research
• Economic evaluation methodologies like cost-effectiveness analysis, cost-utility analysis, and budget impact models

Data Visualization and Communication:

• Data visualization tools such as Tableau, Power BI, or R (ggplot, Shiny), for presenting findings to non-technical stakeholders
• Convey technical results to healthcare professionals, policymakers, and clients

Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Educational Background:
  
  
  • Master's or PhD in a relevant field such as:
  • Data Science
  • Biostatistics
  • Health Economics
  • Epidemiology
  • Public Health
  • Statistics
  • Computer Science or related quantitative disciplines
• 10+ years (for senior roles) of relevant experience in healthcare analytics, HEOR, RWE, or related areas
• Experience with SQL for querying large datasets
• Familiarity with machine learning techniques and tools for predictive analytics
• Knowledge in HEOR & RWE:
  
  
  • Solid understanding of HEOR and RWE methodologies such as cost-effectiveness analysis, burden of illness, treatment pattern analysis, and patient outcome research
  • Knowledge of epidemiological study designs and statistical methods for healthcare data
  • Familiarity with regulatory guidelines related to real-world evidence generation (e.g., FDA, EMA)
• Proficiency in programming languages such as R, Python, or SAS for statistical analysis and data manipulation
• Proficiency in data visualization tools like Tableau, Power BI, or ggplot
• Analytical and Statistical Expertise:
  
  
  • Experience working with large healthcare datasets (claims, EHRs, etc.) and cleaning/manipulating data for analysis
  • Solid foundation in statistical analysis and modeling techniques, including regression analysis, survival analysis, and propensity score matching

Preferred Qualifications:

• Hands-on experience with real-world data sources such as EHRs, claims data, and patient registries
• Experience in life sciences, pharmaceutical consulting, or health economics roles

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 marginalized 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.