Data Analyst

ROK MEDICAL MANAGEMENT LLC is seeking a hands-on Data Analyst to support decision-making with reliable data and practical analytics. This onsite role in Oklahoma City, OK combines day-to-day work in SQL and Python with statistical analysis across the full data lifecycle, from dataset creation to insights shared with both technical and non-technical audiences.

You will build datasets and pipelines, apply quantitative methods to real business and operational questions, and help ensure data quality through validation and troubleshooting. The work also includes identifying opportunities to streamline manual processes and improve the efficiency and scalability of reporting workflows.

• Analyze complex business and operational data to surface trends, explain performance, answer business questions, and deliver actionable insights and reporting
• Write and maintain SQL and Python code to extract, clean, transform, validate, and analyze data from multiple sources
• Develop and maintain trusted datasets, data pipelines, queries, and analytical workflows, including identifying and resolving data quality issues
• Use quantitative and statistical methods to identify and interpret trends, patterns, anomalies, and relationships within complex datasets
• Partner with management and business stakeholders to translate business questions into analytical requirements and prioritize data needs
• Find opportunities to automate manual processes, improve data quality, and make analytical and reporting workflows more efficient and scalable

• Demonstrated experience applying data and quantitative analysis to solve business or operational problems; prior Data Analyst experience preferred, with equivalent technical experience considered
• Strong SQL skills, including querying, joining, transforming, and validating data in relational databases
• Python proficiency for analysis and automation, with experience writing clear, maintainable code (such as using pandas or similar data libraries)
• Working knowledge of statistics and quantitative methods, including selecting appropriate approaches and interpreting results accurately
• Strong analytical and numerical aptitude, curiosity, and attention to detail, with the ability to work through ambiguous problems and large or messy datasets
• Ability to communicate findings clearly and concisely through written summaries, reports, visualizations, and presentations to non-technical stakeholders
• Bachelor's degree in a quantitative or technical field (Engineering, Computer Science, Mathematics, Statistics, Data Science, Economics, Information Systems, or similar); equivalent relevant experience considered

• SQL
• Python
• pandas