Senior Analyst, Insights & Analytics

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes "About The Department" (but we should use heading "About the role"? Actually they said use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to those headings. The posting includes "About The Department" which is about the department, not role. Could treat as "About the role"? Might be okay. There's "The Position" description which is responsibilities. There's "Relationships" maybe part of responsibilities. There's "Essential Functions" which are responsibilities/duties. There's "Physical Requirements" maybe part of qualifications? Could be separate but not in list; we can ignore if not matching headings. There's "Qualifications" section with Required Qualifications: Education, Experience, Specialized Knowledge. That's qualifications. There's no explicit Skills section separate; but we could extract skills from qualifications. Could create Skills section if there is content. There's no Benefits, Pay, Schedule mentioned. So we should not include those sections. We need to use

• for any list of duties/requirements/benefits. So for responsibilities we can list bullet points. For qualifications we can list bullet points. We must preserve all substantive information, not invent or summarize away detail. Must not repeat job title as heading. Must not include boilerplate. We need to strip out navigation etc. The given text includes a lot of content; we need to extract relevant parts. Let's identify sections: - About the department: could be "About the role" (maybe we keep as About the role). Content: paragraph about Marketing & Patient Solutions group, mission, etc. We'll keep that as prose

  . - The Position: description of role: Senior Analyst, Insights & Analytics – Rare Disease serves as primary day-to-day commercial analytics partner... etc. That's responsibilities. - Relationships: details about reporting, stakeholders. Could be part of responsibilities. - Essential Functions: broken into subcategories: Rare Endocrine Analytics Ownership & Business Partnership, Commercial Analytics & Business Performance Insights, Reporting, Data Quality & Self-Service Analytics, AI-Enabled Analytics, Automation & Innovation, Integrated Insights, Communication & Capability Building. These are duties/responsibilities. - Physical Requirements: 10% overnight travel maybe necessary depending on location. On-Site expectation for average of 3 day per week. This could be considered "Schedule"? Actually schedule is about work schedule; physical requirements includes travel and on-site expectation. Could be placed under Schedule? But schedule section is for work hours/shift etc. Not exactly. Since we only include sections when posting has real specific content. There's no explicit schedule like "Full-time, 40 hrs/week". So we might omit Schedule. Physical requirements could be omitted if not matching headings. But we could treat as "Schedule"? Not ideal. Better to omit. - Qualifications: Required Qualifications: Education, Experience, Specialized Knowledge. We'll list bullet points. - No Benefits, Pay. Thus we will output sections: About the role, Responsibilities, Qualifications. We need to use

  for each section heading. Inside each section, we need to use

  for prose and

  • for lists. For About the role: we have prose paragraph(s). We'll put as

    . For Responsibilities: we have many bullet-like duties. We'll create a

    with
    • items covering each essential function bullet and maybe relationship details. We must preserve all substantive information; not invent or summarize away detail. So we need to include all details from the text. Let's extract responsibilities text: From "The Position": - The Senior Analyst, Insights & Analytics – Rare Disease serves as the primary day-to-day commercial analytics partner for assigned U.S. Rare Endocrine Disorders (RED) workstreams, with an initial focus on growth hormone deficiency (GHD). - The Senior Analyst independently owns defined analytical workstreams from business-question framing through execution, interpretation, communication, and follow-through. - The role delivers secondary analytics that inform brand strategy, launch and in-market performance, customer and account opportunity, business reviews, and commercial decisions. - Working within priorities established by the Director and shared portfolio standards, the Senior Analyst maintains direct stakeholder relationships and is accountable for timely, accurate, and decision-relevant outputs within the assigned scope. - A core responsibility is applying and advancing AI-enabled analytics within assigned workstreams. - The Senior Analyst identifies practical use cases and develops or prototypes approved automation, custom GPT/LLM-based assistants, agentic workflows, natural-language analytics, and self-service capabilities that improve speed, consistency, accessibility, or quality while maintaining appropriate validation, governance, and human review. - The Senior Analyst partners with primary market research and specialized analytics functions to integrate relevant evidence into a coherent commercial perspective. - The role also contributes to shared Rare Disease methods, data assets, and scalable capabilities when assigned, without displacing primary RED/GHD accountability. From "Relationships": - This role reports to the Director of U.S. Rare Disease Insights & Analytics and serves as the primary day-to-day analytics partner for assigned RED workstreams, including GHD. - The Senior Analyst builds direct working relationships with Product Directors, Commercial Leadership, Sales Leadership, Forecasting, Finance, Medical Affairs, global insights partners, Enterprise Insights & Analytics, data and technology teams, and other cross-functional stakeholders. - For assigned workstreams, the Senior Analyst independently clarifies business questions, aligns analytical plans and timelines, communicates findings, and follows through on agreed actions. - Material priority, capacity, resource, stakeholder, or business-risk decisions are escalated to the Director. - The Senior Analyst collaborates with the Manager on shared methodologies, portfolio standards, AI-enabled capabilities, cross-portfolio dependencies, and quality review for high-impact priorities. - The Director sets team priorities, resolves material resource tradeoffs, and retains performance-management and development accountability. - The Senior Analyst remains a direct report to the Director and owns assigned analytical workstreams and deliverables end to end. - The Senior Analyst works with the designated primary market research lead and with Field Analytics, Market Access Analytics, and Patient Analytics to coordinate business questions and integrate relevant outputs. - Those functions retain accountability for their respective analytics strategies, methodologies, and deliverables. - Externally, the Senior Analyst may work with data providers, analytics vendors, consultants, and technology partners on defined projects, including scope coordination, quality review, documentation, and delivery. From "Essential Functions" subsections: Rare Endocrine Analytics Ownership & Business Partnership: - Independently owns defined analytics workstreams supporting RED, including GHD, from business-question framing through recommendation and follow-through. - Translates strategic and operational business questions into clear hypotheses, analytical objectives, methods, deliverables, and decision criteria. - Develops and manages workplans, milestones, dependencies, and stakeholder expectations for assigned analyses and recurring deliverables. - Maintains direct stakeholder relationships for assigned workstreams and proactively identifies emerging questions, risks, and opportunities. - Balances recurring and ad hoc priorities in alignment with the Director; escalates material capacity, scope, or timing conflicts with recommended tradeoffs and coordinates shared methodology or cross-portfolio dependencies with the Manager. - Retains accountability for the accuracy, completeness, interpretation, documentation, and timely delivery of assigned analytical outputs. Commercial Analytics & Business Performance Insights: - Integrates and analyzes relevant claims, specialty pharmacy, prescriber, account, product, sales, and other commercial data within the assigned RED/GHD analytics scope. - Develops KPI frameworks, measurement plans, scorecards, and analytical approaches that connect commercial strategy with measurable outcomes. - Conducts analytics supporting launch readiness and tracking, in-market performance, prescriber and account dynamics, customer opportunity, and other commercial performance questions. - Leads preparation of recurring RED/GHD business-performance reviews, translating complex data into clear perspectives on trends, drivers, risks, opportunities, and recommended actions. - Performs prescriber-, account-, product-, and market-level analyses to identify adoption patterns, performance drivers, and commercial opportunities. - Conducts rapid-response and ad hoc analyses for emerging questions, unexpected performance changes, and leadership priorities. - Partners with Forecasting and other functions to connect observed performance and analytical findings with planning assumptions and business discussions. - Ensures conclusions reflect Rare Disease data limitations, including small and concentrated populations, data lag, coverage gaps, longitudinal inconsistency, and uncertainty. Reporting, Data Quality & Self-Service Analytics: - Develops, enhances, and maintains dashboards, scorecards, and reporting tools that provide stakeholders with timely and decision-relevant information. - Applies consistent business definitions, calculation logic, refresh schedules, documentation, and quality controls across assigned deliverables. - Investigates data discrepancies, documents root causes, and coordinates resolution with appropriate data owners and enterprise partners. - Identifies opportunities to simplify recurring reporting, eliminate duplicative work, and automate repeatable analytical processes. - Builds reusable data assets, templates, and self-service capabilities that improve consistency and create capacity for higher-value analysis. - Monitors stakeholder adoption and usefulness of analytics products and recommends improvements based on business needs and feedback. AI-Enabled Analytics, Automation & Innovation: - Contributes to the portfolio AI-enabled analytics roadmap by identifying practical use cases within assigned RED/GHD workstreams. - Develops or prototypes approved automation, custom GPT/LLM assistants, agentic workflows, natural-language analytics, and data-connected workflows using authorized platforms. - Connects data to approved workflows and tests, validates, documents, and monitors AI-supported outputs with human review and analytical accountability. - Partners with the Manager and appropriate enterprise governance functions to support compliant implementation. - Creates reusable guidance and supports adoption of approved AI-enabled and self-service capabilities by analysts and authorized stakeholders. - Measures impact through cycle time, analytical capacity, quality, consistency, adoption, and decision support and recommends whether capabilities should be refined or scaled. Integrated Insights, Communication & Capability Building: - Synthesizes secondary analytics, primary market research, forecast assumptions, and other cross-functional inputs into a coherent view of commercial performance. - Develops leadership-ready presentations that distinguish evidence, interpretation, implications, risks, opportunities, and recommended actions. - Communicates complex methods, limitations, and findings in accessible business language for commercial and cross-functional audiences. - Presents analyses and facilitates working sessions that help stakeholders move from information to aligned action. - Exercises objective analytical judgment, constructively challenges assumptions, and clearly distinguishes verified findings from assumptions or hypotheses. Physical Requirements (maybe ignore). Now Qualifications: Required Qualifications: Education Bachelor’s degree required in business, analytics, data science, economics, life sciences, public health, healthcare, or a related field. Experience Minimum of 2 years of progressive pharmaceutical or biopharmaceutical experience in commercial analytics, secondary analytics, business intelligence, data strategy, or a closely related function. Experience independently managing defined analytical workstreams from business-question framing through execution, interpretation, communication, and follow-through. Experience partnering directly with commercial stakeholders and translating ambiguous questions into structured analytical plans and actionable recommendations. Experience supporting launch-stage and/or in-market brands through KPI development, business reviews, prescriber or account analytics, customer opportunity assessment, or dashboard strategy. Hands-on experience using de-identified patient-level claims and pharmaceutical commercial data—such as IQVIA, Komodo, specialty pharmacy, prescriber, account, product, or sales data—to answer business questions. Experience translating complex data into decision-relevant findings, implications, and recommendations. Hands-on experience developing or prototyping automation, GenAI/LLM, agentic, natural-language analytics, or comparable AI-enabled workflows and evaluating output quality. Experience managing multiple priorities, timelines, dependencies, and stakeholder expectations in a fast-paced environment. Experience coordinating with matrixed partners, vendors, consultants, or enterprise analytics and technology teams. Specialized Knowledge Strong understanding of pharmaceutical commercial analytics, including performance measurement, customer and market analytics, launch tracking, and secondary-data limitations. Understanding of Rare Disease analytical challenges, including small and concentrated populations, clinical complexity, data lag, coverage gaps, longitudinal inconsistency, and uncertainty. Ability to