• Partner with business to gather requirements and implement solutions • Collaborate with IT teams and prioritize projects • Lead cross-functional teams and manage multiple projects • Establish system documentation standards and quality assurance methodologies

Role Description Perform high-quality medical record abstraction by combining proficient-level experiences in data management and software with medical terminology, medical coding, information encoding, and analytical capabilities. Interpret and manage complex clinical patient data for research, quality improvement, and regulatory reporting. - Data Abstraction: Accurately review, interpret, and abstract clinical patient data from various electronic health record (EHR) systems, paper charts, and other source documents in accordance with defined project or research protocols, clinical, data, and technical specifications, and dictionaries. - Coding and Classification: Apply knowledge of medical coding systems (e.g., ICD-10, MedDRA, CPT, HCPCS) and standard of care guidelines to interpret, classify, and categorize abstracted clinical data points from unstructured text to standardized machine-readable data in one common database schema. - Electronic Data Capture (EDC): Utilize specialized data management software (e.g., REDCap, registries, and custom-built EDC systems) to enter, track, and maintain the integrity of clinical data encoded into queryable databases. - Technical Support: Aid cross-functional teams in translating clinical and data abstraction and encoding requirements. Support prompt engineering and design for all AI and LLM initiatives. - Data Management: Apply and support establishing program-specific clinical data management best practices (CGDMP) and good clinical practice (GCP) during the abstraction and encoding process resulting in accurate, legible, contemporaneous, original, attributable, complete, and consistent for end-to-end ETL workflows. - Quality Assurance and Control: Apply industry standard best practices for utilizing real-world data for research, quality monitoring, and regulatory reporting using technical and analytical software such as running MACROs and using Excel/Google Sheets functions and formulas, and pivot tables to support ensuring abstracted data are accurate and clinically complete. - Mentoring and Subject Matter Expertise (SME): Conduct peer reviews on medical record data interpreted and encoded by abstraction peers to ensure quality and productivity performance align with the program's expectations. - Protocol Adherence: Maintain strict adherence to all project and research protocols, institutional review board (IRB) requirements, HIPAA regulations, data management best practices (e.g., DAMA, SCDM, ACRP, and SOCRA), and organizational policies regarding patient privacy and data security. - Process Improvement: Participate in the development and refinement of abstraction and quality guidelines, tools, and standard operating procedures. - Daily Operations: Provide timely and accurate daily, weekly, or monthly abstraction submissions, productivity reporting, and actively participate in team meetings and workshops. - Certifications: Maintenance of all relevant clinical or technical licensures. - Other duties and responsibilities to be performed as assigned. Qualifications - Clinical Background: U.S. licensed Nurse, PA-C, NP, or DNP is required with a Master’s degree in health sciences. Strong understanding of medical terminology, disease processes (especially cancer), standard clinical workflows, and genetic testing. - Clinical Experience: Minimum of 4-5 years of experience in clinical data abstraction and medical records review, preferably in cancer, women’s health, rare diseases. - Data Abstraction Expertise: Proven ability to accurately read, interpret, and abstract complex clinical information from various electronic and paper medical record sources. - Data Management Expertise: Direct experience performing clinical data encoding using standard ontologies including but not limited to ICD-10-CM and SNOMED CT. Direct experience performing data mapping, standardization, and harmonization. - Quality and Compliance: Demonstrated commitment to data integrity, quality control processes, and adherence to HIPAA and other data privacy regulations. - Technical Proficiency: Proficient with Microsoft Office Suite or Google Suite, creating pivot tables, generating reports, data analysis, and using clinical data systems or databases common in clinical data abstraction, research, or clinical data management (e.g., fillable forms, ECDs, data registries). - Certifications/Industry Expertise: CCDM, CCRP, ACR-P, or CRA preferred. - Communication: Excellent written and verbal communication skills, with the ability to effectively collaborate with clinical and non-clinical teams. - Autonomy: Proven ability to work independently, manage time effectively, prioritize and organize tasks, and meet strict productivity and quality deadlines. - General Expertise: Possess a high level of initiative and self-motivation. Capable of working part of a team on high visibility projects and tasks with high rates of communication. In-depth attention to detail and a fast learner. Responding to shifting priorities and changes. Requirements - The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications, and specific office location. This may differ in other locations due to cost of labor considerations. - Remote USA: $130,600 — $163,300 USD Benefits - Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. - Natera employees and their immediate families receive free testing in addition to fertility care benefits. - Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits, and much more. - Generous employee referral program! Company Description Natera™ is a global leader in cell-free DNA (cfDNA) testing, dedicated to oncology, women’s health, and organ health. Our aim is to make personalized genetic testing and diagnostics part of the standard of care to protect health and enable earlier and more targeted interventions that lead to longer, healthier lives. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers, and many other professionals from world-class institutions, who care deeply for our work and each other. When you join Natera, you’ll work hard and grow quickly. Working alongside the elite of the industry, you’ll be stretched and challenged, and take pride in being part of a company that is changing the landscape of genetic disease management.

• Regularly design, develop, and maintain data pipelines and ML workflows to support operational and analytical needs • Write clean, efficient, and well-documented Python code for data processing, model development, and automation tasks • Analyze and interpret complex datasets, including time-series and machine health data to surface meaningful insights and support decision-making • Build, validate, and monitor AI/ML models in production, proactively identifying and resolving performance issues • Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across teams • Participate in cross-functional meetings and planning sessions to align data engineering efforts with broader business goals • Stay current with advancements in AI/ML techniques, tools, and industry-specific applications, particularly within power, oil, and gas environments • Document processes, models, and systems in a way that supports knowledge sharing and team continuity

• Manage day-to-day IT operational services, ensuring stability, availability, and performance of critical systems and infrastructure. • Monitor operational KPIs, SLAs, OLAs, and service quality metrics. • Coordinate incident, problem, change, and service request management processes. • Lead operational governance meetings and service review sessions. • Ensure operational compliance with internal standards and IT governance frameworks. • Lead process mapping initiatives for IT operations and service management workflows. • Analyze current-state processes and design optimized future-state operational models. • Identify process gaps, inefficiencies, bottlenecks, and operational risks. • Document end-to-end workflows, SOPs, RACI matrices, and operational procedures. • Standardize operational routines and governance practices across teams. • Identify recurring operational issues and implement corrective and preventive actions. • Coordinate root cause analysis (RCA) and continuous service improvement plans. • Support transition from project delivery into stable operational support models. • Ensure operational readiness for new services, applications, and infrastructure deployments. • Identify automation opportunities across operational and service management processes. • Partner with infrastructure, cloud, DevOps, and engineering teams to implement automation solutions. • Improve operational efficiency through workflow automation, monitoring enhancements, and self-service capabilities. • Promote a culture of continuous improvement and operational excellence. • Support implementation and optimization of ITSM and monitoring tools. • Establish and maintain strong operational routines with key business and IT stakeholders. • Act as the primary point of contact for operational service discussions and escalations. • Facilitate recurring governance meetings, status reviews, and executive reporting. • Ensure clear communication of operational performance, risks, and improvement initiatives. • Build collaborative relationships across technical and business teams.