Lead Data Scientist

Presbyterian Healthcare Services

3d•$117,915 - $206,918•Onsite

About The Position

Presbyterian Healthcare Services is seeking a Lead Data Scientist to identify opportunities for innovative descriptive, prescriptive, and predictive analytics based on market developments and business needs, and to manage analytical projects in collaboration with other Analytics Organization directors. The role collaborates across the organization on exploration and experimentation, prototypes, analytical solutions, and best practices. It guides development of models supporting real-time, data-driven business decisions, mentors junior scientists, and supports senior leadership in evaluating, developing, and implementing analytics that generate actionable insights. Based at the Reverend Hugh Cooper Administrative Center in Albuquerque, New Mexico, this exempt, full-time position works day shifts. The Lead Data Scientist serves as a subject matter expert across healthcare analytics domains and leads advanced modeling, analytics initiatives, and the translation of findings into operational strategies and measurable outcomes. The role partners with internal and external stakeholders, develops visualizations and self-service analytics, leads analytical work in program evaluation and system implementations, and mentors analysts and data scientists. Presbyterian Healthcare Services is a locally owned, not-for-profit healthcare system with nine hospitals, a statewide health plan, and a multi-specialty medical group. It was founded in New Mexico in 1908 and has nearly 14,000 employees. The organization states that it is committed to improving the health of the communities it serves.

Requirements

Bachelor’s degree in econometrics, biostatistics, computer science, applied mathematics, engineering, physics, or another quantitative field.
Eight or more years of experience in business intelligence, statistical analysis, predictive modeling, and business strategy; a relevant master’s degree may substitute for two years, a Ph.D. for four years, and a fellowship for an additional two years.
Demonstrated expertise in machine learning, artificial intelligence, and statistical analysis, including hypothesis testing, experimental or quasi-experimental design, and advanced mathematical modeling.
Experience developing predictive and analytical models using classification, regression, survival analysis, recommender systems, forecasting, optimization, and A/B testing.
Strong experience with Python, R, SQL, SAS, Tableau, and relational and NoSQL databases.
Strong knowledge of healthcare data, healthcare analytics, and industry standards including HL7, FHIR, LOINC, ICD-9/10, CPT, DRGs, and ETGs.
Experience leading complex healthcare analytics projects involving ETL, data cleansing, data mapping, business intelligence, and data-driven strategies to improve decisions and operational performance.
Strong executive-level communication and presentation skills, including the ability to translate complex analytics into clear recommendations for senior and C-suite leadership.

Nice To Haves

Master’s or Ph.D. in a quantitative field.
Experience with Hadoop, Spark, Kafka, Storm, graph databases, or other big data technologies.
Proficiency with SAS or similar analytics software and data visualization tools such as Tableau or Power BI.
Expertise across multiple healthcare analytics domains, such as risk adjustment, clinical program effectiveness, and care management analytics.
Experience mentoring analysts and scientists on the use, interpretation, and integration of advanced analytical models.
Experience developing strategic, proactive, self-service analytics solutions and translating findings into actionable business strategies.
Advanced experience analyzing clinical, financial, and administrative data for exploratory and hypothesis-driven studies.
Strong presentation and communication skills for conveying complex analytical findings to senior leadership and diverse audiences.

Responsibilities

Serve as a subject matter expert and thought leader across healthcare analytics domains, including program evaluation, care management, clinical, operational, and financial analytics.
Lead the design and development of advanced analytical solutions using statistical modeling, machine learning, forecasting, optimization, and predictive and descriptive modeling.
Analyze complex structured and unstructured clinical, financial, and administrative data to identify trends, patterns, risks, and opportunities.
Develop, test, validate, and continuously enhance predictive and analytical models supporting business and clinical decision-making.
Translate analytical insights into actionable operational strategies, workflows, and measurable business outcomes.
Partner with business leaders, IT, vendors, academia, and government partners on strategic analytics initiatives.
Create data visualizations and self-service analytics solutions for operational teams and senior leadership.
Lead analytical components of program evaluations, workflow optimization, change management, and healthcare analytics system implementations.
Mentor and develop analysts and data scientists, providing technical and analytical guidance and leadership.
Stay current on analytics technologies and methodologies and identify opportunities to improve organizational value and support strategic initiatives.
Identify opportunities for innovative analytics and manage analytical projects in coordination with other Analytics Organization directors.
Collaborate across the organization on exploration, experimentation, prototypes, analytical solutions, and best practices.
Support senior leadership in evaluating, developing, and implementing reporting, research, and analytics solutions.