The Clinical Oncology Data Analyst is responsible for the development, quality, and effectiveness of the data entering, and the analytics resulting from clinical data sets. Reporting to the Senior Director, Clinical Data Services, this role will work with the Data Services team to interpret and organize clinical oncology data. This role will be responsible for assisting with the development of data capture forms and feasibility tests.
This role works directly with the Data Services and HEOR teams to ensure high quality data is abstracted into the clinical data sets to meet the internal and external needs of the clients. This role will collaborate with the statistician and HEOR specialist to perform required analytics and reporting to meet project deliverables.
- Engages with external clients to understand RWE data needs and internal capabilities to deliver on projects.
- Serves as expert on data flow, structure, availability, schemas, and clinical abstraction requirements.
- Supports data quality and control activities, including correcting errors and refining instructions.
- Works with VP of Business Development to ascertain needs and goals of clients.
- Works with internal HEOR team to drive high quality analytics. Performing analyses as needed and learning new advanced techniques.
- Participated in day to day meetings, communications and internal team interactions.
- Minimum of a BS in science, nursing, or healthcare related field; MS strongly preferred
- At least 3 years of relevant experience as a clinical research assistant, registered nurse, nurse practitioner, physician assistant, or equivalent with considerable healthcare experience and specifically experience in oncology
- Minimum of 5 years of analytics experience
- Demonstrated data analytic capabilities; statistical analytic capabilities preferred
- Experience with clinical data management
- High comfort level with technology and familiarity with EMR systems
- Exceptional attention to detail
- Self-motivator who can prioritize and address problems in a highly dynamic and fast-paced environment
- Availability for off hours coverage and occasional travel
- Statistical analytic capabilities preferred
- Proficient with Microsoft Office, SQL; Familiar with SAS, Python, R