Director, Life Sciences Analytics and Solutions

Vizient•Centennial, CO

1d•$117,600 - $206,000

About The Position

The Director, Life Sciences Analytics and Solutions provides technical and analytical leadership in designing, developing, and scaling advanced healthcare analytics solutions for Vizient’s life sciences consulting, research, and data product offerings. The role combines expertise in large-scale healthcare claims data, advanced analytical methods, and modern data platforms to address complex business challenges and expand analytical capabilities. The position leads development of analytical solutions for client-specific consulting engagements, recurring data deliveries, and scalable analytical models. Work includes longitudinal patient journey analyses, patient and provider segmentation, integration of new data sources, and reusable analytical assets. The role also improves the accessibility, efficiency, and utility of data assets by converting fragmented datasets into streamlined analytical frameworks and partnering with consulting, data science, engineering, and product teams. The Director applies technical expertise, healthcare domain knowledge, and independent problem-solving to make complex analytical work repeatable and scalable. The role leads concurrent technical workstreams from feasibility and solution design through development, validation, and delivery, while communicating risks and dependencies, engaging stakeholders, mentoring colleagues, and influencing analytical standards.

Requirements

Bachelor’s degree in a relevant field preferred.
At least 7 years of related experience working with large-scale healthcare data, including administrative claims, clinical, or other longitudinal healthcare datasets.
Advanced experience developing healthcare analytics using SQL and Python, with experience using Spark and Databricks or comparable large-scale data processing platforms.
Demonstrated experience developing longitudinal patient analyses, cohort methodologies, patient or provider segmentation, attribution methodologies, risk adjustment, statistical modeling, or similar advanced healthcare analytics.
Strong understanding of healthcare claims structures, coding systems, patient populations, utilization patterns, and the strengths and limitations of healthcare data.
Experience transforming complex or fragmented datasets into standardized, reusable analytical models and assets.
Strong analytical problem-solving skills, including the ability to independently navigate incomplete data, ambiguous requirements, methodological limitations, and complex business questions.
Strong communication and consulting skills, including the ability to explain sophisticated analytical work.

Nice To Haves

Advanced degree in analytics, statistics, data science, epidemiology, health economics, computer science, healthcare informatics, or a related field.
Demonstrated ability to convert custom analytical work into repeatable, automated, and scalable methodologies or solutions.
Experience partnering across consulting, product, engineering, data science, technology, or similar cross-functional teams to deliver analytical solutions.

Responsibilities

Lead the design, development, and execution of complex analytical solutions using large-scale administrative claims, clinical, and other healthcare datasets.
Develop longitudinal patient journey analyses, disease and treatment progression models, patient and provider segmentation methodologies, cohort identification frameworks, patient attribution, risk adjustment, and statistical models.
Translate complex business and client requirements into validated, reusable datasets, analytical models, and methodologies for research, consulting engagements, dashboards, applications, and client-facing products.
Lead the transformation and optimization of large healthcare datasets using Databricks and related platforms, consolidating fragmented data into streamlined and reusable analytical models.
Design and optimize complex SQL, Python, and Spark workflows supporting large-scale claims processing, longitudinal research, advanced analytics, and standardized patient-, encounter-, provider-, and organization-level datasets.
Establish practical standards for analytical documentation, data lineage, table grain, join keys, data quality, testing, validation, version control, refresh cadence, reproducibility, and appropriate-use limitations.
Transform complex consulting engagements into repeatable methodologies, standardized workflows, automated recurring deliveries, and reusable analytical assets for Vizient tools, products, and client solutions.
Partner with consulting, product, engineering, data science, and technology teams to integrate new data sources, improve processing and delivery efficiency, operationalize analytical prototypes, and expand scalable analytics capabilities.
Serve as a technical and healthcare data subject matter expert, providing guidance on claims structures, coding systems, patient populations, utilization patterns, longitudinal analyses, data-use limitations, and interpretation of analytical findings.
Independently lead concurrent technical workstreams from feasibility and solution design through development, validation, and delivery.
Communicate risks and dependencies, engage internal and external stakeholders, mentor colleagues, and influence analytical standards across teams.