
Senior Clinical Data Analyst (Healthcare Analytics)
- Chicago, IL
- $102,000-138,000 per year
- Permanent
- Full-time
- Gather requirements, conduct data sourcing, cleaning, and quality assurance of data output.
- Build, automate, and maintain data extracts, reports, dashboards, and self-service products.
- Collaborate with Data Scientists in exploring operational improvement opportunities and creation of predictive models and applications.
- Act as a single point of contact and support the needs of the Operations Teams of Tendo's customers.
- 5+ years of experience working in clinical data analytics in a healthcare setting.
- One of the following:
- Bachelor's in Computer or Data Science, Engineering, Business/Finance, or Health Sciences.
- Master's in Public Health, Data Science, Business Administration, or Statistics.
- Relevant work experience and portfolio of projects.
- Core Competencies:
- Use and configuration of business intelligence tools (PowerBI, Business Objects: Crystal Reports, Universe, and Web intelligence tool preferred).
- Proficiency in SQL querying and data manipulation, including Stored Procedures and Query optimization (Microsoft preferred).
- Electronic Health Record (EHR) Analytics (Epic Clarity and Caboodle highly desired).
- Must be able to work independently and in a team setting.
- Knowledge of Clinical Documentation in EHR and the ability to extract data based on workflow description.
- Excellent communication skills.
- Proven excellence in working simultaneously with multiple clients and on multiple projects.
- Experience working in a professional software environment using source control (git), an issue tracker (JIRA, Confluence, ServiceNow, Azure DevOps, etc.), continuous integration, code reviews, and agile development process (Scrum/Lean).
- Experience with AWS technology stack (S3, Glue, Athena, EMR, etc.).
- Knowledge of, or experience with, healthcare data standards such as HL7, FHIR, ICD, SNOMED, LOINC.
- Experience with Delta Lake and/or Databricks.
- Experience using Apache Spark (PySpark or Scala).
- Experience working with programming languages (Python).
- Experience with machine learning workflows and data requirements for use with ML frameworks.