Data Analyst I SaS ONSITE ONLY
Houston, TX
Full Time
Experienced
Data Analyst I
Type: Full‑Time, exempt
Location: On‑site (Required and no relocation applies)
Focus: Retrospective Clinical / Healthcare Data Analysis
** This is not a remote position! This is onsite only M-F**
Please do not email your resume, All candidates must complete an application to be considered.
We are seeking a Data Analyst I to support retrospective clinical and healthcare analytics projects. This role involves extracting and preparing large healthcare datasets, conducting SAS‑based statistical analyses, and collaborating with clinical and research teams to generate high‑quality, analysis‑ready outputs. Ideal candidates have strong analytical skills, hands‑on experience with healthcare data, and familiarity with modern data tools.
Key Responsibilities
Required Skill Set
Data Extraction & Preparation
Type: Full‑Time, exempt
Location: On‑site (Required and no relocation applies)
Focus: Retrospective Clinical / Healthcare Data Analysis
** This is not a remote position! This is onsite only M-F**
Please do not email your resume, All candidates must complete an application to be considered.
We are seeking a Data Analyst I to support retrospective clinical and healthcare analytics projects. This role involves extracting and preparing large healthcare datasets, conducting SAS‑based statistical analyses, and collaborating with clinical and research teams to generate high‑quality, analysis‑ready outputs. Ideal candidates have strong analytical skills, hands‑on experience with healthcare data, and familiarity with modern data tools.
Key Responsibilities
- Extract, clean, validate, and manage clinical/healthcare datasets.
- Prepare analysis‑ready datasets using SQL, Python, or PySpark.
- Conduct SAS‑based statistical analyses and produce TLFs.
- Interpret results and support clinical and research decision‑making.
- Maintain thorough documentation, QC checks, and compliance with HIPAA/PHI.
Required Skill Set
Data Extraction & Preparation
- Strong experience with SQL (joins, window functions, performance‑tuned queries).
- Ability to extract, clean, and prepare large healthcare datasets (EHR, claims, provider/member).
- Experience working in cloud environments (Azure or AWS).
- Preferred: Databricks, PySpark, Delta Lake, Unity Catalog, workflow orchestration.
- Preferred: Python (Pandas, NumPy, Matplotlib).
- Proficiency in Base SAS and SAS/STAT.
- Ability to generate TLFs, summary tables, and statistical outputs for retrospective studies on large datasets.
- Experience supporting Statistical Analysis Plans (SAPs) and related documentation.
- Strong understanding of descriptive and inferential statistics.
- Bachelor’s or Master’s in Statistics, Biostatistics, Data Science, Public Health, Healthcare Informatics, or related field.
- 3+ years of experience working with clinical, epidemiological, or healthcare datasets.
- Strong analytical, documentation, and problem‑solving skills.
- Adhere to HIPAA/PHI handling standards and least‑privilege data access.
- Follow internal governance, IRB, and data use agreements where applicable.
- Maintain secure storage, version control, and reproducible analysis practices.
- Experience with Azure Data Factory.
- Familiarity with HL7/FHIR standards.
- Understanding of HCC risk adjustment.
- Exposure to predictive analytics or machine learning in healthcare.
- Experience with Power BI or Tableau for study reporting/monitoring.
Equal Employment Opportunity Statement
We are an Equal Opportunity Employer and make employment decisions based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other status protected under applicable federal, state, or local law.
Work Authorization Requirement
Applicants must be currently authorized to work in the United States on a full-time basis. At this time, we are unable to sponsor or assume sponsorship of employment visas now or in the future.
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