[Hiring] Senior Manager, Quality Assurance @Alnylam Pharmaceuticals

Role Description

Support real world data analyses across multiple late stage and marketed assets, including design and execution of the following types of analyses:

• Treatment patterns and drug utilization
• Resource utilization
• Adherence and persistency
• Survival
• Cost-effectiveness
• Comparative effectiveness
• Burden of disease
• Indirect treatment comparisons (e.g., network meta-analysis, quantitative bias assessment)

Collaborate with cross-functional colleagues (Epidemiology, Biostatistics, HEOR, Medical Directors, Market Access) in delivering analytics and insights using medical claims and electronic health records.

Develop payer-facing analytic tools and models. Develop evidence to support key value messages. This position supports the design and conduct of real-world data (RWD) analyses focused on pharmaceutical and biotechnology products that are in late-stage clinical development (Phase III or Phase IV) or have already received regulatory approval (i.e., marketed products). These products include therapies in the rare disease space (e.g., transthyretin amyloidosis, porphyria, and other genetic disorders), and the work is conducted in the biopharmaceutical industry, specifically in the area of Health Economics and Outcomes Research (HEOR).

Conduct Real-World Evidence (RWE) Analyses:

• Design and execute real-world data studies using large-scale healthcare databases (e.g., Medicare, Optum Clinformatics, Truven MarketScan, Truveta electronic health records).
• Develop protocols and statistical analysis plans and write and QC computer programs (e.g., SAS, Snowflake) to analyze treatment patterns, healthcare resource use, medication adherence and persistency, patient survival outcomes, and economic burden of disease.
• Apply advanced statistical methods such as network meta-analysis and quantitative bias adjustment techniques to conduct indirect treatment comparisons.

Develop Payer-Facing Models and Tools:

• Build economic models and budget impact tools that simulate costs and outcomes associated with the use of the company's therapies compared to standard of care.
• These tools are used by payer organizations and health technology assessment bodies for coverage and reimbursement decisions.

Contribute to Publications and Scientific Communications:

• Draft abstracts, manuscripts, and conference posters to disseminate study findings.
• Ensure scientific rigor and compliance with regulatory and ethical standards.

Collaborate with cross-functional colleagues:

• Work with cross-functional stakeholders (including Epidemiologists, Biostatisticians, Medical Affairs, and Market Access teams) to generate evidence that supports the product’s value proposition to payers and regulatory agencies.

Supervisory Responsibility:

• The position does not supervise other employees and does not involve assigning work to subordinates.
• However, the role may mentor junior team members or collaborate with external vendors (e.g., data analytics firms or contract research organizations) without formal supervisory responsibilities.

Qualifications

• Master’s degree in Pharmacy, Economics, Biostatistics, epidemiology, or related field of study and six (6) years of work experience in the job offered or related occupation in which the required experience was gained.
• In lieu of a Master’s degree, a PhD in Pharmacy, Economics, Biostatistics, epidemiology, or related field of study and four (4) years of work experience in the job offered or related occupation in which the required experience was gained will be accepted.
• Demonstrated experience in the following:
• BI content promotion and project support
• Administrating, supporting, troubleshooting, installing, configuring, and programming SAS
• Working with BI tools and Data Integration
• SAS applications installation and project migration
• Windows and UNIX Servers in supporting SAS users
• Real-world healthcare database research
• Synthesizing multiple healthcare data sets to generate new insights in evidence to support commercial objectives
• Statistical modelling of observational healthcare data sets
• SAS programming

Company Description