Scientific Account Executive

Company introduction: Compass Pathways plc (Nasdaq: CMPS) is a biotechnology company dedicated to accelerating patient access to evidence-based innovation in mental health. The Company is headquartered in London, UK, with offices in New York City in the US. We focus on developing novel treatments that have the potential to improve the lives of those who are suffering with mental health conditions and who are not helped by current treatments.   We are pioneering a new paradigm for treating mental health conditions focused on rapid and durable responses through the development of our investigational COMP360 synthetic psilocybin treatment, potentially a first in class treatment. COMP360 has Breakthrough Therapy designation from the US Food and Drug Administration (FDA) and has received Innovative Licensing and Access Pathway (ILAP) designation in the UK for treatment-resistant depression (TRD) due to the pressing unmet need in this area. We are currently in phase 3 for TRD, have completed phase 2 studies for both post-traumatic stress disorder (PTSD) and anorexia nervosa and are planning a further late-stage study in PTSD. We envision a world where mental health means not just the absence of illness but the ability to thrive. - Compass Pathways. Job overview:   The Field-Based Health Economics & Outcomes Research (HEOR) Science Liaison is a scientifically trained, field-based expert, serving as a scientific bridge to external healthcare decision makers (HCDMs), including MCOs, PBMs, IDNs, ACOs, SPPs, and HTA bodies. The HEOR Science Liaison delivers credible, non-promotional scientific exchange across clinical evidence, real-world evidence (RWE), pharmacoeconomics, and health outcomes to support informed formulary, coverage, and reimbursement decisions. The role spans the full product lifecycle and is key to demonstrating the value of innovative therapies to payer and access stakeholders. Location: Remote in the United States. Reports to: Director, HEOR. Roles and responsibilities  (Include but are not limited to):  External Scientific Engagement * Identify, cultivate, and maintain peer-to-peer relationships with key payer thought leaders, formulary decision makers, Chief Medical Officers, Chief Pharmacy Officers, and other HCDMs within assigned geography * Deliver fair-balanced, scientifically rigorous presentations on clinical data, real-world evidence, pharmacoeconomic models, budget impact analyses, and patient-reported outcomes (PROs) * Respond to unsolicited medical information requests from payer and access stakeholders with accurate, compliant, and timely scientific content * Attend and represent the organization at managed care, payer, and scientific conferences to maintain awareness of current landscape issues and emerging data HEOR Evidence Generation & Dissemination * Partner with internal HEOR, RWE, and Medical Affairs teams to identify evidence gaps and support the design, execution, and dissemination of field-based observational studies, retrospective analyses, and pharmacoeconomic research * Facilitate investigator-initiated and collaborator-initiated research proposals; coordinate with appropriate internal stakeholders for review and approval * Support development and communication of health economic models, cost-effectiveness analyses, and budget impact tools for payer audiences * Contribute to publications, posters, and abstracts for scientific meetings and peer-reviewed journals Payer Landscape Intelligence & Insights * Gather and synthesize field intelligence on evolving payer policies, formulary decisions, coverage criteria, value-based contracting trends, and competitive landscape dynamics * Communicate insights to internal stakeholders including Medical Affairs, Market Access, HEOR, and Commercial teams to inform strategy and evidence planning * Monitor and interpret changes in managed care regulations, government payer policy (CMS, Medicare, Medicaid, VA/DoD), and HTA methodologies Cross-Functional Collaboration & Training * Serve as a scientific resource to Market Access Account Directors, Commercial teams, and other field-based colleagues; provide training on disease state, clinical data, and health economics topics * Collaborate with Medical Science Liaisons (MSLs), Global Medical Affairs, and HEOR headquarters teams to align field activities with overarching medical strategy * Appropriately collaborate with the Market Access team to educate and inform payers about clinical and health economic aspects of Compass Pathways’ investigational and on-market products * Participate in advisory board activities, scientific symposia, and payer-focused medical education programs * Complete all required training, compliance reporting, and administrative responsibilities in accordance with corporate policy and applicable law Candidate Profile:  * Advanced degree required, M.D., D.O., Pharm.D., or Ph.D. preferred, in a relevant scientific or health-related discipline (health economics, pharmacoeconomics, epidemiology, health services research, public health, or clinical sciences) * Minimum 2-3 years of experience in the capacity of field-based liaison, working with a pharmaceutical company, presenting to and engaging with payer customers, in collaboration with the Market Access function * Minimum 3–5 years of experience in managed care, PBM, CMS/Medicare/Medicaid/VA/DoD, health care consulting, pharmaceutical industry, or a related access/HEOR environment * Demonstrated knowledge of health economics methodology, including cost-effectiveness analysis, budget impact modeling, QALYs, systematic reviews, and meta-analyses * Strong understanding of the US payer landscape, formulary management, and reimbursement processes * Proven ability to translate complex scientific and economic data into clear, compelling narratives for payer and access audiences * Valid driver’s license and ability to travel 50–70% of the time by car and air 【For NYC】Compensation Description (annually): Please note that the base salary range is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. Base pay is one part of the Total Package that is provided to compensate and recognise employees for their work and any role at Compass, regardless of the location, is eligible for additional discretionary bonuses and equity. 【Base salary per annum】: $160,000—$195,000 USD BENEFITS & COMPENSATION: For an overview of our benefits package and compensation information, please visit  "Working at Compass".   EQUAL OPPORTUNITIES:  Reasonable accommodation We are committed to building a workplace where everyone’s wellbeing matters. If you need reasonable accommodation during the interview process to be at your best, please let our recruiting team know.  UK applicants We are proud of our commitment to diversity and equality (pursuant to the Equality Act 2010). We do not discriminate based upon race, religion or belief, colour, nationality, ethnic or national origin, gender, pregnancy or maternity, marital or civil partner status, sexual orientation, gender reassignment, age or disability. US applicants Compass Pathways is proud to be an equal opportunity employer. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, and related medical conditions), ethnicity, age, disability, sexual orientation, gender identity, gender expression, military service, genetic information, familial or marital status, or any other status, category, or characteristic protected by applicable law. SPONSORSHIP: Unfortunately, we cannot sponsor employment visas and can only accept applications if you have employment rights in the country to which you are applying. DATA PRIVACY: All data is confidential and protected by all legal and data privacy requirements, please see our recruitment Privacy Notice to learn more about how we process personal data.

Grafana Labs, the company behind the open observability cloud, is founded on the principles of open source, open standards, open ecosystems, and open culture. Grafana Cloud, our fully managed observability platform, is flexible and built for scale. With Grafana Cloud's actually useful AI, organizations can see, understand, and act on all their disparate data to move at the speed of their ambitions. Today, more than 35 million users and 7,000+ customers – including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce – trust Grafana Labs to ensure reliability of their applications and systems, resolve incidents quickly, and optimize their telemetry to reduce noise and cost. We are a 100% remote company with 1,600+ team members across 40+ countries, and we’re backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com [http://grafana.com] and follow us on LinkedIn [https://www.linkedin.com/company/grafana-labs/] and X [https://twitter.com/grafana]. We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. SENIOR ML ENGINEER RECOMMENDER SYSTEMS, DEVELOPER ADVOCACY | US | REMOTE This is a fully remote position and we're considering candidates in the US. The Opportunity: Grafana Labs is building an Interactive Learning system, an open source, in-product learning experience that helps users learn and succeed without leaving Grafana. A central part of that vision is a personalized recommendation system that helps each user discover the next guide, action, or product experience most likely to help them succeed. Today, the Interactive Learning tool includes a rule-based recommendation engine that provides useful contextual recommendations. We are hiring an ML Engineer to lead its evolution into an increasingly personalized, continuously improving system driven by real-time product behavior, content metadata, customer context, and experimentation. This is an applied product data science role. You will personally build, deploy, and operate recommendation models, design experiments, establish evaluation methodology, and define the scientific roadmap. You will partner closely with software engineers who own the production recommender codebase and with an existing Data Analyst who supports measurement, instrumentation, and analysis across Developer Advocacy. What You’ll Be Doing: The long-term vision is ambitious, but we do not expect it to arrive in one release. We are looking for someone who can understand the whole problem, establish strong foundations, and ship measurable improvements into the existing recommender one iteration at a time. * Evolve the Interactive Learning Plugin's recommendation system * Develop increasingly personalized approaches to candidate selection, ranking, sequencing, and next-best-action recommendations. * You’ll own a real-time recommendation service * Build and operate applied models * Develop, validate, version, monitor, and iterate on models used by the recommendation system. * You’ll own model training & serving * Define what recommendation quality means * Develop offline, online, and longitudinal measures of recommendation performance. * You’ll own feature pipelines, monitoring of the model and architecture * Ship incremental improvements * Use the data and infrastructure available today while identifying the instrumentation and platform capabilities needed tomorrow. * Integrate improvements into the existing recommender rather than waiting for a complete replacement system. * Partner across disciplines * Work closely with software engineers & data analysts to productionize models and integrate them safely into the recommender service. * Partner with the Product Analytics team on metric definitions, instrumentation, data quality, dashboards, and experiment analysis. * Collaborate with Developer Advocacy, Docs, Product, Engineering, GTM, and other teams to translate ambiguous needs into testable hypotheses and measurable product decisions. * Explain modeling choices, tradeoffs, uncertainty, and results clearly to both technical and non-technical audiences. What Makes You a Great Fit: We know it is rare to find everything. Strong candidates should demonstrate credible ability across all three core areas below and be particularly strong in at least two. * Recommendation and personalization science: you have built recommendation, ranking, search, matching, propensity, or next-best-action systems.  You are comfortable beginning with simple, explainable approaches when they are the best way to learn. * HTTP/gRPC, streaming, Go/TypeScript previous experience in distributed systems * Applied model ownership.  You have personally built, validated, monitored, and iterated on models used in a product or operational environment. You can work effectively in version-controlled codebases and collaborate with engineers on production implementation. You should also be a strong product thinker and technical communicator. You can take an ambitious and ambiguous objective, identify the most important unknowns, and create a sequence of models and experiments that steadily improves the product. Bonus Points For: * Experience with content, education, onboarding, or learning recommendation systems * Experience with SaaS product telemetry and customer-account data * Experience using warehouse-scale behavioral data * Experience with directed graphs, sequence models, or prerequisite-aware recommendations * Experience with contextual bandits or other exploration strategies * Familiarity with Grafana or the broader observability ecosystem * Experience with open source software or transparent development practices * Experience working with privacy, fairness, explainability, or responsible personalization constraints Compensation & Rewards: In the United States, the base compensation range for this role is $154,445 - $185,334. Actual compensation may vary based on level, experience, and skillset as assessed throughout the interview process. All of our roles include Restricted Stock Units (RSUs), giving every team member ownership in Grafana Labs' success. We believe in shared outcomes—RSUs help us stay aligned and invested as we scale globally. *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: * 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. * Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. * Transparent Communication – Expect open decision-making and regular company-wide updates. * Innovation-Driven – Autonomy and support to ship great work and try new things. * Open Source Roots – Built on community-driven values that shape how we work. * Empowered Teams – High trust, low ego culture that values outcomes over optics. * Career Growth Pathways – Defined opportunities to grow and develop your career. * Approachable Leadership – Transparent execs who are involved, visible, and human. * Passionate People – Join a team of smart, supportive folks who care deeply about what they do. * In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it.  * Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy [https://grafana.com/legal/applicant-and-candidate-privacy-policy/].