• Shape the data science roadmap: Identify measurement, audience, and AI capabilities that create value in each specialty market, and build a function that scales with the business. • Build causal lift measurement: Own the framework that demonstrates how HCP engagement drives real-world prescribing change — matched and synthetic controls, lookalike populations, methodologies defensible to pharmaceutical medical affairs and legal, and repeatable across therapeutic areas. • Build decisioning and personalization systems: Develop next-best-action, recommendation, and audience intelligence models that personalize the HCP experience and identify high-value audiences for sponsor targeting at scale. • Apply LLMs and generative AI across the workflow: Use them for structured extraction, feature engineering, insight generation, and HCP profile enrichment — wherever they cut time-to-insight without compromising rigor. • Translate findings into commercial products: Turn model outputs into sponsor-facing measurement reports, audience intelligence packages, and ROI dashboards, and present methodology directly to pharmaceutical medical affairs and commercial teams. • Own the ML platform layer: Feature engineering, experiment tracking, model registry, A/B and holdout frameworks, and production monitoring on the company's cloud and data warehouse stack.

• Join us in redefining what it means to work for a CRO. • Work closely with the multidisciplinary project team across the life cycle of the project to ensure data management is thoughtfully planned and delivered in a consistent, timely, and high quality manner. • Key contributor to project success through development and utilization of innovative tools to help automate manual tasks and identify data trends in a timely fashion. • Constant collaboration with project peers, particularly biostatisticians, statistical programmers, and clinical operations personnel. • Independently perform and oversee completion of data management tasks to ensure clinical database design supports project outcomes. • Proactively clean clinical trial data and mitigate risks. • Effectively communicate data-related decisions to sponsors and ensure data management activities follow all applicable standards and project-specific procedures.

• 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 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.