Director - Diagnostic Quality Analytics & Reporting

Role Summary

The Director of Diagnostic Quality Analytics & Reporting will build and lead the data, analytics, and reporting backbone that powers Caris’ end-to-end assay quality oversight. This role owns the strategy and execution for data curation, engineering, visualization, and advanced analytics to track, trend, and report daily quality signals—including wet lab bench metrics, sequencing yield, performance of controls and personnel, operator, environmental, and other key performance indicators of the Caris commercial assays. Partnering closely with Quality, Lab Operations/Management, and Executive Leadership, the Director will architect the dashboards, automated alerts, and narrative reporting that drive proactive decision-making, audit readiness, and continuous improvement across lab operations.

Responsibilities

• Design, implement, and maintain robust data ingestion, transformation, and presentation pipelines that unify assay QC/QM data from LIMS, instruments, environmental sensors, and production systems; ensure, auditability, and SLA-based reliability.
• Define canonical data models and metrics dictionaries for assay performance, control behavior, environmental conditions, and process capability; implement versioned datasets with change management.
• Establish automated data quality checks, schema validation, and anomaly detection to ensure trustworthy reporting.

• Build and govern enterprise dashboards and self-service data marts that provide run-level to executive-level visibility (daily/real-time where appropriate) into assay health and trends.
• Implement SPC charts, capability indices (Cp/Cpk), Pareto analyses, funnel plots, and trend lines to surface emerging issues and variation drivers.
• Develop automated alerting/notifications (e.g., threshold or model-based) for abnormal conditions across instruments, operators, sites, and assays.
• Produce concise weekly/monthly executive narratives and inspection-ready Quality reports with clear insights, actions, and ownership.

• Regularly perform exploratory analysis, forecasting, and root-cause investigations; partner with Quality to translate findings into CAPA actions and verify effectiveness via measurable signal shifts.
• Lead deep dives on failure modes (by assay step, instrument, reagent lot, operator, or environment) and quantify impact on yield, TAT, and patient-impact risk.
• Collaborate with Lab Management to design experiments (e.g., A/B, DoE) for process improvements; quantify ROI and operational impact.

• Build and mentor a small, high-performing team.
• Own the roadmap, backlog, and operating cadence for quality analytics; define OKRs, uptime/refresh SLAs, and stakeholder satisfaction metrics.
• Champion a culture of data integrity, transparency, and continuous improvement.

Qualifications

• MS/PhD in Data Science, Biostatistics, Computer Science, Biomedical Engineering, or related field (or BS with significant equivalent experience).
• Strong data visualization (ggplot2 preferred, Seaborn, Altair acceptable).
• Experience in creating reports using Tableau (preferred) or PowerBI.
• Proficient in extracting data from a variety of sources, including Linux file systems, AWS s3, MySQL databases, ad-hoc Excel spreadsheets and the ability to rapidly visualize desired content.
• 7+ years building production-grade analytics solutions in diagnostics, medical devices, pharmaceuticals, or high-throughput labs.
• Expert Python (pandas, NumPy, SciPy), SQL, and data engineering fundamentals (ETL/ELT, APIs).
• Proven expertise with enterprise dashboard packages (data modeling, DAX/LOD, governance, performance tuning, time-series analysis).
• Hands-on experience with control charts/SPC, reliability/quality analytics, and statistical testing; familiarity with DoE preferred.
• Experience integrating data from LIMS, instruments, and environmental monitoring systems; familiarity with GxP/CSV practices.
• Working knowledge of CLIA/CAP, 21 CFR 820, ISO 13485, MDSAP, and IVDR requirements as they relate to data, metrics, and documentation.
• Basic understanding of Next Generation Sequencing.

Additional Requirements

• Must possess ability to sit, stand, and/or work at a computer for long periods of time.
• May require occasional after-hours work to meet deadlines and ensure delivery of patient and enterprise data.