Senior Data Quality Analyst
New York City, New York City
Applications have closed
Tempus
Tempus has built the world’s largest library of clinical & molecular data and an operating system to make that data accessible and useful, starting with cancer.Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
We now have more healthcare data than ever before, but providers often do not have the systems or expertise to make sense of all of this valuable data. At Tempus, we are building the infrastructure to modernize and enhance cancer treatment. We are on a mission to connect an entire ecosystem to redefine how data is used to improve patient outcomes. The Clinical Informatics team is seeking a highly-motivated data analyst who enjoys working with complex datasets and building quality assessment tools and help improve the utility of the data generated from our pipelines.
What you’ll do:
As part of the informatics team, you’ll play a key role in helping us develop and deploy an overarching data quality management strategy for real world data aggregated from a variety of sources. This will include the development of quality monitoring metrics and the establishment of routine reporting activities. Key objectives of your continuous quality assessment and improvement initiatives will be ensuring data completeness and maximizing data fidelity as we build the largest library of oncology clinical data in the world. You’ll work with clinical data experts, data architects, engineers, data scientists, and informatics analysts to ensure the quality of our data for analysis downstream.
Responsibilities:
- Collaborate with cross functional teams to identify and develop methods to measure data quality across the organization
- Adapt and deploy quantitative and qualitative methods based on existing standards and best practices
- Automate reporting on quality assurance metrics to enable cross-team coordination and resolution of data quality issues
- Support the enrichment and semantic normalization of data assets
- Analyze the useability of our data and generate insights that can be leveraged to further improve its utility
Skills and Qualifications:
- Master's degree in a STEM discipline
- 3+ years of Python/SQL/R experience
- Data quality analytics and reporting experience
- Experience working with health data
- Extremely high attention to detail and fast learner
Nice-to-Have:
- Knowledge of Health Informatics
- Experience with Standard Medical Terminologies (SNOMED-CT, ICD-9/10, LOINC, etc.)
#LI-EV1
Tags: Data quality Pipelines Python R SQL STEM
Perks/benefits: Team events
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