Sr. AI & Data Science Analyst

Job Summary

The Senior AI and Data Science Analyst serves as the driver of AI innovation and advanced data science and analytics within the US Commercial organization.

This role leads the design, development, and deployment of next‑generation analytical capabilities that shape business strategy, enhance field execution, and accelerate data‑driven decision making

This role focuses on shaping business requirements, defining analytical use cases, and translating data into actionable insights, leveraging AI capabilities and partnering with IT for implementing new analytical solutions.

This analyst will be the primary intelligence partner for the US Rare Disease and IG Selling teams, ensuring field personnel have timely, actionable insights to improve customer engagement, optimize performance, and support growth. The role blends strategic thinking, deep analytical acumen, and hands‑on execution—ideal for someone passionate about transforming data into impact.

What you'll do

AI, Automation & Advanced Analytics Leadership

• Identify, evaluate, and propose AI and advanced analytics use cases to improve forecasting
• Evaluate, and deploy emerging AI and advanced science methodologies that improve forecasting, targeting, lead generation, call planning, and customer engagement.
• Build scalable infrastructure and repeatable processes for advanced analytics within rare disease and corporate account functions.
• Partner with Business Intelligence, IT, and other company functions to align on data strategy and maximize value from enterprise data assets.

Rare Disease & Corporate Accounts Strategic Support

• Act as the primary analytical advisor to rare disease field teams, national account directors, and corporate account leadership.
• Design dashboards, KPIs, opportunity analytics, payer/access insights, and account performance reporting.
• Translate complex trends into clear, actionable recommendations for field teams and leadership.
• Understand rare disease market nuances—small patient populations, access challenges, prescriber dynamics—and tailor analytical solutions accordingly.

Field Operations Enablement

• In collaboration with IT, develop intelligent tools and insights that enhance field execution (territory analytics, customer segmentation, target lists, performance drivers).
• Run deep-dive analyses on pull‑through, barriers, referral flows, and account-level dynamics.
• Lead analytic workstreams during product launches, major business shifts, or organizational changes.

Cross‑Functional Collaboration & Influence

• Collaborate with Sales, Marketing, and Finance to align insights and ensure consistent commercial strategy execution.
• Communicate findings to senior leadership with clarity and strategic framing.
• Drive adoption of AI- and analytics-enabled tools by training field teams and stakeholders.

Operational Excellence

• Own development, maintenance, and enhancement of critical commercial analytics assets in strong collaboration and partnership with IT.
• Ensure timely delivery of regular and ad‑hoc insights.
• Maintain strong data quality, documentation, and process scalability.

Qualifications and need-to-know

Required

• Bachelor’s degree in quantitative or business field (Statistics, Analytics, Economics, Engineering, Business, etc.).
• 5+ years of experience in commercial analytics, business intelligence, or related roles within biopharma or healthcare.
• Proven experience with AI/ML, analytics, advanced modeling, or automation tools.
• Technical skills: SQL, Python/R, Power BI/Tableau, and familiarity with cloud data environments, experience with AI Platforms.
• Expertise in synthesizing complex datasets and delivering insights to field teams or commercial leaders.
• Exceptional communication skills and ability to influence without authority.

Preferred

• Experience in rare disease analytics, or corporate account strategy.
• Background supporting field-facing teams (sales, national accounts, payer access).
• Familiarity with CRM, patient-level datasets, specialty pharmacy networks, and claims analytics.
• Exposure to generative AI, advanced forecasting, or optimization algorithms.