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xCures

Oncology data platform for treatment decisions

AI Quality Engineer

Quantitative Biology & BiostatisticsConfirmed live in the last 24 hours
Full-timeRemote in USA

About the Job

Requirements

  • Strong background in computational biology, bioinformatics, or a related life sciences discipline, through formal education or hands-on experience.
  • Strong clinical knowledge across major disease areas, including diagnostic criteria, staging or severity classifications, and standard-of-care treatment patterns.
  • Experience with electronic medical records and the current healthcare data landscape, including Health Information Exchanges and Qualified Health Information Networks.
  • Experience with structured clinical data and real-world data analysis.
  • Knowledge of data quality principles and data validation processes, and ability to assess the provenance and limitations of real-world data.
  • Proficiency in Python, R, or SQL for data manipulation and analysis.
  • Ability to translate complex scientific concepts into clear, actionable findings for technical and non-technical audiences.
  • Strong written and verbal communication skills.
  • Ability to manage multiple complex, unrelated projects at once, with strong organization and time management.
  • Comfort working remotely with virtual collaboration tools.

Responsibilities

  • Lead ongoing quality control of clinical extractor outputs, running systematic accuracy and consistency analyses across detection, dataset composition, and value extraction, and resolving discrepancies before they reach clients.
  • Lead regulatory alignment for the extraction and validation program, keeping quality processes, methodology, and documentation consistent with applicable privacy, de-identification, and clinical-data standards.
  • Lead client-facing performance reporting, translating validation metrics and extractor capabilities and limitations into clear, evidence-backed reports for client and internal audiences.
  • Serve as an internal subject-matter expert for clinical domains, with an emphasis on oncology and real-world evidence, guiding the Data Science team on interpretation, clinical relevance, and the limits of current extraction methods.
  • Partner with Data Science to prototype and refine extraction logic, inferred variables, normalization, and binning, contributing domain expertise on the nuances of medical text.
  • Define and monitor clinical quality key performance indicators, track extractor performance drift over time, and recommend retraining or recalibration when the data warrants it.
  • Work with Engineering and Clinical Informatics to ensure accurate export of structured clinical data into downstream formats such as FHIR bundles and CSV tables.
  • Support data governance and dataset integrity, contributing to data-dictionary alignment, de-identification, and the quality of clinical datasets used for development and delivery.
  • Serve as a clinical reviewer in internal quality reviews, client demos, and quality assurance events, and support business development with feasibility analysis for prospective and current clients.

Desired Qualifications

  • Four or more years of relevant industry experience.
  • Master's degree in computational biology, bioinformatics, or a life sciences discipline.
  • Experience with medical coding ontologies such as SNOMED, LOINC, RxNorm, or OMOP.
  • Familiarity with version control using Git or GitHub and collaborative code workflows.
  • Comfort in a command-line environment and cloud development tools such as AWS, GCP, or similar.
  • Experience defining or reporting quality and performance metrics for AI or data-extraction systems.
  • Familiarity with de-identification methods such as HIPAA Safe Harbor or Expert Determination, and clinical data governance.

About the Company

xCures

Oncology data platform for treatment decisions

xCures uses artificial intelligence to help doctors and researchers improve cancer care. It provides a platform that automatically extracts, normalizes, and structures real-time medical data to support treatment decisions. The product ingests diverse data from providers, researchers, and pharmaceutical companies and turns it into clear, actionable insights for oncologists and cancer patients. Unlike others, xCures focuses on real-time, large-scale cancer data and fragmented medical records to enable precision medicine and faster access to critical information. The company licenses its AI-powered platform through subscriptions and offers data analytics services to its clients. Its goal is to turn complex healthcare data into clinically useful insights that improve patient outcomes and support investigational cancer treatments and precision medicine guidelines.

Company size
51-200
Company stage
Series B
Total funding
$58.7M
Headquarters
Oakland, CA
Founded
2018

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