Data Compliance Engineer

MUST HAVE HEALTHCARE EXPERIENCE
W-2 ONLY. NO C2C or 3rd party agencies.
6 month contract, fully remote.

We are looking for someone who can do data segmentation exercise in python, so this person must be familiar with data handling and processing libraries and some statistical modeling in python. Most of the data that needs to be analyzed is in SQL server.

Job Description
We are seeking a mid-level Statistician to support data analytics initiatives across both clinical and operational domains. This role involves applying statistical methods to healthcare quality, safety, and performance data, enabling data-driven decision-making and continuous improvement. The ideal candidate will have strong analytical skills, healthcare experience, and proficiency in Python.

• Perform statistical analyses on both clinical and operational datasets to identify trends, patterns, and performance insights.
• Develop and validate statistical models to support healthcare quality measurement, risk adjustment, and operational efficiency.
• Collaborate with cross-functional teams-including clinical, research, and administrative staff-to define analytical goals and interpret results.
• Create dashboards, reports, and visualizations using Python, Power BI, and other tools to communicate findings effectively.
• Ensure data integrity and compliance with healthcare regulations (e.g., HIPAA).
• Contribute to the development of data collection strategies and analytics frameworks for both patient care and operational workflows.
• Support data governance initiatives by promoting data quality, consistency, and compliance across clinical and operational datasets.

Required Skills

• Bachelors or Master's degree in Statistics, Biostatistics, or a related field.
• 5-7 years of experience in statistical analysis within the healthcare industry.
• Proficiency in Python is required, including libraries such as pandas, NumPy, and statsmodels.
• Experience working with healthcare data (e.g., EHRs, claims) and operational data (e.g., staffing, throughput, resource utilization).
• Familiarity with SQL and data visualization tools (e.g., Power BI, Excel).
• Strong communication skills with the ability to present complex data to both technical and non-technical audiences.
• Ability to manage multiple projects and collaborate effectively in interdisciplinary teams.