Senior Data Scientist

Health Management Associates•St. Paul - CD, MN

About The Position

The Senior Data Scientist I investigates and resolves complex healthcare data issues across client implementations, regulatory reporting, operational processes, and data integration workflows. The role analyzes healthcare data, SQL code, ETL processes, technical specifications, and business rules to identify root causes, validate processing results, and recommend solutions that support data accuracy, client deliverables, operational processes, and encounter submission capabilities. The Senior Data Scientist collaborates with technical, operational, client service, and business teams; documents findings and recommendations; and communicates analytical results to technical and non-technical audiences. The role also serves as a subject matter resource for assigned clients, data domains, business rules, and processing methodologies.

Requirements

Bachelor’s degree in data science, biostatistics, epidemiology, computer science, mathematics, statistics, information systems, healthcare informatics, or a related field.
At least 5 years of experience working with healthcare data, analytics, data investigation, data quality, reporting, or data integration processes.
At least 3 years of experience developing and analyzing SQL queries.
Advanced SQL query development and data analysis skills.
Ability to review and understand complex SQL code, ETL processes, data transformations, and business rule implementations.
Knowledge of healthcare claims, encounter, enrollment, eligibility, provider, financial, and regulatory-reporting data.
Ability to perform root-cause analysis and resolve complex data and processing issues.
Ability to interpret technical specifications, business requirements, data structures, and processing workflows.
Strong written and verbal communication skills.
Strong interpersonal skills and ability to work effectively with technical and non-technical stakeholders.
Strong project management, organization, and time management skills.
Ability to manage multiple projects, investigations, and priorities concurrently.
Strong problem-solving, analytical, and critical-thinking skills.
Strong attention to detail and commitment to delivering accurate, high-quality work.
Ability to learn new business domains, systems, and data structures quickly.
Self-motivated, with a commitment to continuous learning and process improvement.
Ability to use technology and AI tools ethically and effectively to improve efficiency, quality, and processes while protecting confidential information and applying sound judgment.

Nice To Haves

Experience with healthcare claims, encounter, enrollment, eligibility, provider, financial, or regulatory-reporting data.

Responsibilities

Investigate and resolve complex healthcare data issues, discrepancies, and operational questions.
Perform root-cause analysis by reviewing source data, SQL code, ETL processes, business rules, and processing workflows.
Analyze claims, encounter, enrollment, eligibility, provider, and financial data to identify trends and data issues affecting client deliverables and operational processes.
Write and maintain complex SQL queries for data validation, analysis, troubleshooting, reconciliation, and reporting.
Review data transformations, ETL processes, technical specifications, and business rules to identify data quality and processing issues.
Validate processing results and recommend corrective actions to improve data accuracy and reporting.
Collaborate with developers, analysts, operations teams, client service teams, and business stakeholders to define problems, evaluate impacts, and implement solutions.
Translate analytical findings into recommendations that support data integration, reporting, operational processes, and encounter submission capabilities.
Serve as a subject matter resource for assigned clients, data domains, business rules, and processing methodologies.
Document findings, recommendations, data issues, business rules, and resolutions.
Communicate technical and analytical findings to technical and non-technical audiences.
Prepare analysis and supporting documentation for internal stakeholders, clients, and project teams.
Perform other duties as assigned.