• Own our CI/CD systems end-to-end: audit the current state, redesign where needed, and drive measurable improvements in pipeline reliability, build/test cycle time, and overall developer experience within the first six months • Lead the adoption of standardized QE practices and testing frameworks across engineering teams, reducing inconsistency in coverage and establishing a shared standard for quality across the organization within your first year • Drive increased automation of QE processes using AI-assisted tooling (such as Claude, Codex, or Cursor), accelerating development velocity while maintaining rigorous standards • Lead, mentor, and grow a team of 1–3 Quality Engineers: supporting their technical development, career growth, and day-to-day effectiveness, with a goal of visibly improving team velocity and reducing defect escape rates • Partner closely with Engineering and Product to shift quality earlier in the development lifecycle, building a culture where defect prevention is prioritized over defect detection • Establish structured knowledge sharing and process documentation that enables the team to scale its impact beyond its headcount

Role Description The Quality Assurance & Training Specialist, Porting is responsible for designing, delivering, and continuously improving training and quality assurance programs for Porting support operations. This role supports both internal team members and BPO partners, ensuring consistent, high-quality customer interactions and operational accuracy. This position combines training development, performance evaluation, and data-driven coaching to strengthen representative effectiveness and improve customer outcomes. Qualifications - Experience in customer support quality assurance, training, or enablement - Strong analytical skills with the ability to interpret data and translate insights into action - Excellent written and verbal communication skills, including facilitation and coaching - Ability to manage competing priorities across QA, training development, and delivery - Experience working with tools such as Zendesk, AutoQA, LMS platforms (e.g., WorkRamp), and knowledge management systems (e.g., Notion) Requirements - Design, develop, and maintain Porting training programs aligned with product functionality, carrier workflows, and operational standards - Partner with Training & QA stakeholders to define and evolve the porting-specific curriculum, ensuring new hires ramp quickly on carrier processes, LOA requirements, and internal tools - Deliver onboarding and ongoing training sessions for new and tenured Porting representatives - Collaborate on onboarding certification design, defining readiness criteria and key milestones for handling live porting requests independently - Create and manage enablement resources, including WorkRamp courses and Notion documentation - Partner with subject matter experts to ensure training content reflects current product features, processes, and branding - Share frontline insights (e.g., carrier quirks, rejection trends, policy updates) to keep training content current and practical - Review and contribute to external-facing knowledge base content to ensure alignment with internal guidance - Conduct weekly manual QA evaluations in Zendesk AutoQA (target: 4 evaluations per representative per week) - Provide ongoing input into QA scoring criteria and participate in calibration sessions to ensure standards reflect current carrier expectations, regulatory requirements, and customer experience goals - Analyze QA results and audit trends to identify performance gaps, root causes, and systemic knowledge issues - Translate QA insights into actionable recommendations for team leads, managers, and training initiatives - Partner with Training to develop targeted coaching materials, refresher modules, and updated reference guides based on QA findings - Support performance improvement through 1:1 coaching sessions, small group facilitation, and team-level trainings in partnership with CX leadership - Monitor quality and training effectiveness using QA data and performance metrics - Identify gaps in knowledge, process, or tooling and recommend scalable solutions - Continuously refine QA scorecards, training materials, and coaching approaches to improve outcomes - Advocate for appropriate QA coverage and resources as the Porting function scales, ensuring evaluation capacity keeps pace with volume growth Benefits - The total on-target-earnings for this position range from $86,000-$101,000, plus equity and benefits. - This range is designed to align with market rates in areas where we are actively recruiting across the USA. - The range displayed reflects the target for new hire salaries, and within this range, individual pay is determined by your skills and experience, as well as relevant education. - Your recruiter can share more and answer questions about the specific salary range during the hiring process. - Salary is just one component of Quo’s total compensation package. - Your total rewards package will include equity, extensive medical coverage, a monthly lifestyle stipend, and a flexible PTO policy.

• Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical). • Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types. • Work closely with the R&D team to understand data requirements and address data quality concerns. • Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications. • Evaluate and validate external public data sources, ensuring they meet quality standards. • Stay up-to-date with the latest data quality best practices and tools in the biological domain.

• Data Validation Pipeline Development: Develop and implement comprehensive data validation protocols for diverse biological datasets (histology, omics, clinical). Ensure data integrity, consistency, and accuracy through rigorous quality checks. Design and implement automated data quality pipelines to streamline data validation and identify potential issues early in the data processing workflow. • Data Curation & Standardization: Establish and enforce data standardization practices to facilitate seamless integration and analysis across different data types. Curate datasets to enhance their usability for machine learning. • Collaboration & Communication: Work closely with the R&D team to understand data requirements and address data quality concerns. Communicate data quality findings and recommendations effectively to technical and non-technical stakeholders. Communicate and synchronize with external data providers. • Documentation & Reporting: Maintain a detailed documentation of the data-quality assessment procedures, validation results, and data specifications. Generate regular reports on data quality metrics and trends. • Data Source Evaluation: Evaluate and validate external public data sources, ensuring they meet our quality standards and are suitable for inclusion in our foundation model training. • Continuous Improvement: Stay up-to-date with the latest data quality best practices and tools in the biological domain. Propose and implement improvements to our data- quality assessment processes and pipelines.