Associate Director, Advanced Analytics Global Rare

Alnylam Pharmaceuticals

1d • $164,000 - $221,800

About The Position

Join the Alnylam Commercial Data and Analytics team and help build a product-driven engine that turns data-driven insights into deployed decisions with measurable business impact. As part of Customer Experience and Innovation, you will work cross-functionally with technical and business partners to accelerate commercial outcomes by standardizing what we build, how we build it, and how we deliver it through the tools and workflows business users rely on every day.
As Associate Director, Advanced Analytics Global Rare, you will be the key analytics strategic partner for Rare business leaders in the US, international, and emerging markets. You will collaborate fluidly with Commercial Data and Analytics Value Teams to deliver and manage decision products that enable specific business outcomes such as advanced patient finding, competitive performance understanding, and improved patient engagement. Your in-depth understanding of disease areas, commercial data sources, and Rare business objectives will ensure robust integrated delivery for headquarters, customer, and patient-facing teams.
In this role, you will bring product thinking to analytics end-to-end. You will be deeply embedded with the business to lead discovery and problem framing, define decision logic and success measures, and partner with engineering and platform product management to deliver analytics that are adopted, measurable, and continuously improved. You will work within and across multiple Value Teams, leading on specific outcomes while also building reusable analytical components and shared standards that accelerate delivery across the broader portfolio.
The position will be based in Cambridge, MA.

Requirements

• BS degree in Business, Data Science, Computer Science, Engineering, Information Systems, or related field, or equivalent experience.
• 9+ years in commercial advanced analytics or data science, ideally in healthcare or life sciences.
• Strong product-thinking and cross-functional delivery skills, including discovery, prioritization, measurement discipline, and adoption-focused enablement.
• Advanced proficiency in SQL and Python or R, and comfort with modern analytics tooling such as Spark and dbt for analytics engineering and metric standardization.
• Experience with AI and ML frameworks and APIs, and partnering with engineering to productionize analytics and support monitoring.
• Experience using AI tooling to improve throughput and quality, including responsible use of agentic AI analytics and AI-native IDEs.
• Experience with healthcare data such as EHR, administrative claims, and laboratory data, including common vendors and datasets.
• Strong measurement and inference skill set, including experimentation, causal inference, uplift modeling, optimization, or advanced forecasting as relevant to commercial and patient decisions.
• Proven ability to communicate complex insights to diverse audiences, including senior executives, with strong attention to detail and problem-solving skills.
• Experience working in Jira and collaborating using git-based version control in GitHub.

Responsibilities

• Work within and across multiple Value Teams, aligning to transparent priorities and delivering reusable analytics that scale across franchises and markets.
• Own analytics product strategy and roadmap for assigned decision products: identify the highest-leverage decisions, size opportunity, and sequence releases to maximize impact and adoption.
• Lead complex decision-product analytics such as patient-finding algorithms, competitive dynamics and share shifts, account opportunity prioritization, and patient journey risk forecasting, with outputs embedded into core workflows.
• Drive end-to-end product framing for decision-focused use cases: user definition, problem statement, hypotheses, decision points, and success metrics that combine value and adoption.
• Translate business needs into deployable analytic requirements, including thresholds, segmentation logic, trigger definitions, measurement plans, and learning loops that improve over time.
• Deliver decision-ready insights with clear storytelling and stakeholder-ready visuals, including executive-level readouts that drive decisions and follow-through.
• Partner with engineering to move prototypes into production and define expectations for monitoring, retraining, and operational performance where models are involved.
• Partner with Data Stewardship to define and use single source of truth metrics, ensure traceability to governed definitions and gold-layer data products, and contribute to analytics engineering using dbt-informed specifications and documentation.
• Use AI tooling to increase efficiency and throughput, including AI-native IDEs and safe use of agentic AI analytics when appropriate; operate in agile delivery rhythms using Jira and GitHub-based version control for analytic artifacts.

Benefits

• We offer comprehensive benefits including medical, dental, and vision coverage, life and disability insurance, a lifestyle reimbursement program, flexible spending and health savings accounts and a 401(k)with a generous company match.
• Eligible employees enjoy paid time off, wellness days, holidays, and two company-wide recharge breaks.
• We also offer generous family resources and leave.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees