• This is a senior operational leadership role with responsibility for compliance, governance, data integrity and operational assurance across the business. • You’ll own how compliance and operational governance are designed, embedded and continuously improved across Tiro. • You’ll work across the full operational ecosystem: - apprenticeship funding compliance - governance and operational controls - audit readiness and assurance - learner data integrity and reporting - ILR, PDSAT and funding submissions - compliance operations and process design - systems improvement and automation - operational risk management - cross-functional operational alignment - regulatory readiness across the learner journey

Role Description Courtyard is hiring a Staff Data Scientist to own pricing across our portfolio collectibles. Pricing is load-bearing at our business — it touches revenue and operational decisions daily, with direct financial consequences. This role builds and improves our pricing methodology across a large, heterogeneous catalog of often-thinly-traded assets. You'll partner closely with engineering on our pricing pipeline, with operations on real-world feedback loops, and with the rest of the data team on measurement and evaluation. - Own and evolve pricing models across asset categories, including designing approaches for new and sparsely-traded asset types - Build data quality and anomaly detection systems for adversarial and corrupted external data inputs - Ship production code into our pricing pipeline and services in partnership with engineering - Partner with operations, finance, and product on pricing-related decisions across the company Qualifications - Strong foundations in applied statistics, economics, or signal processing — robust estimation, state-space models, sparse/hierarchical data, anomaly detection, and uncertainty quantification - Backgrounds of interest: quantitative trading, fraud/anomaly detection, computational neuroscience or physics — in addition to traditional pricing or marketplace DS - Track record owning a production scoring or pricing system end-to-end - Production-grade Python and SQL; comfort working inside a real codebase and shipping models into continuously-running services - Experience with sparse, irregular, heterogeneous, or adversarial data - Pragmatism about modeling — right tool for the data you actually have - 5+ years of industry experience or Ph.D. - Bonus: experience sourcing heterogeneous external data via API or scraping Benefits - A dynamic and engaging environment focused on fostering real growth and innovation - Opportunities to create amazing products that our customers truly love and value - Comprehensive health insurance packages with dependent coverage - Competitive salary with ample opportunities for career advancement and development - Enjoy the flexibility of a fully remote work environment - 401(k) plan with a 4% employer match to help you plan for the future - $100 monthly dogfooding stipend to support trying out our products firsthand - Access to employee wellness programs designed to support your overall well-being

Role Description The Systematic Review Scientist will lead and support high-quality evidence synthesis projects, with a strong emphasis on meta-analyses and network meta-analyses. This role requires deep methodological expertise combined with a forward-looking mindset. The successful candidate will be comfortable leveraging artificial intelligence (AI) and automation tools to increase efficiency, consistency, and scalability across the evidence synthesis lifecycle. Primary Position Responsibilities: - Design, conduct, and report systematic reviews in accordance with methodological best practices (e.g., PRISMA, Cochrane, GRADE). - Perform pairwise meta-analyses and network meta-analyses, including model selection, assessment of heterogeneity, inconsistency, and sensitivity analyses. - Develop and execute reproducible workflows for literature searching, screening, data extraction, and risk-of-bias assessment. - Lead or contribute to protocol development, statistical analysis plans, and final reports/manuscripts. - Collaborate with clinical experts, statisticians, and stakeholders to ensure methodological rigor and relevance. - Apply AI-enabled tools (e.g., machine-learning–assisted screening, data extraction, LLM-based summarization) to streamline review processes while maintaining quality and transparency. - Evaluate, validate, and refine AI workflows to ensure appropriate use, auditability, and methodological integrity. - Stay current with advances in evidence synthesis methods, statistical approaches, and AI applications. - Mentor less experienced staff and contribute to internal methodological standards and guidance, as appropriate. - Provide support, project management, subject-matter expertise and liaison services to assigned Committees and/or Councils. - Ability to perform work in alignment with ASA core values: Dedication, Collaboration, Commitment to Excellence, Continuous Improvement. Qualifications - Bachelor’s degree in related field required. Master’s degree in Public Health, Epidemiology, Statistics, Health Economics, or related discipline preferred. - Minimum 5 years of experience with health care research. - Demonstrated experience conducting systematic reviews and meta-analyses including hands-on experience with network meta-analysis. Published peer-reviewed systematic reviews and/or network meta-analysis is preferred. - Strong understanding of evidence synthesis standards, risk-of-bias tools, and reporting guidelines. - Experienced user of Microsoft Office products: Word, Excel, and PowerPoint. - Proficiency with statistical software used for meta-analysis (i.e., R, Stata, SAS, or equivalent). - Experience using reference management and systematic review platforms (i.e., EndNote, Covidence, DistillerSR, Rayyan, or similar). - Familiarity with reproducible research practices (i.e., version control, reproducible code) is preferred. - Experience working with guideline development, HTA, or regulatory contexts is preferred. - Practical experience using AI or machine-learning-enabled tools to support systematic review tasks (i.e., screening, data extraction, summarization, quality checks) is preferred. - Ability to design efficient, scalable workflows that integrate AI while preserving methodological rigor and transparency is preferred. Benefits - Quality medical, dental, and vision insurance at a reasonable cost. - 401K match. - Free fitness center. - Breastmilk shipping. - CALM subscription. - Volunteer committees. - Employee resource groups. - More detailed benefits information can be found at: ASA Benefits . Company Description The American Society of Anesthesiologists (ASA) team provides education, resources, and advocacy to help our members improve the experience and safety of patients in their care. ASA has been named one of the Best and Brightest Companies to Work For in Chicago and the Nation® for the past ten years. ASA offers flexible hybrid work arrangements, a "dress for your day" mindset, generous time off, plus professional development and educational benefits.

• Design, deploy, and scale data science solutions across the organization. • Support best practices across the team. • Work closely with Digital and Marketing teams, converting ideas into experiments and models into shipped product features. • Lead technical discussions and drive engineering best practices across the team.