Senior Principal Statistical Programming Lead

Biogen

Chicago (IL)

On-site

USD 141,000 - 188,000

Full time

4 days ago

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Benefits offered by this job

Medical, Dental, Vision, & Life insurr

Fitness & Wellness programs

Short- and Long-Term Disability

Paid vacation and year-end shutdown

12 holidays + 3 personal days

80 hours sick time

Maternity and Parental Leave

401(k) with company match

Employee stock purchase plan

Tuition reimbursement up to $10,000

Employee Resource Groups

Job summary

Biogen is seeking a Senior Principal Analyst, Statistical Programming to lead programming activities across studies and external vendors, ensuring timely, compliant deliverables and data standardization. You will guide ADaM/define.xml development, support regulatory submissions, and drive best practices across teams worldwide.

Ideal candidates have deep SAS expertise, CDISC standards mastery, and strong leadership in a global, fast-paced environment.

Qualifications

Bachelor's degree required; advanced degree preferred.
10+ years of pharmaceutical/biotech/CRO experience in clinical data analysis and programming.
10+ years of hands-on SAS programming experience (Base SAS; SAS STAT, Macro, Graph).
10+ years supporting clinical trials across multiple phases.
5+ years working with clinical databases and data structures.
CDISC SDTM and ADaM expertise; regulatory submission deliverables.

Responsibilities

Lead and oversee programming activities across studies or programs with internal teams and external vendors.
Serve as Statistical Programming Lead for one or more clinical programs, managing milestones and resources.
Manage programming deliverables from database build through regulatory submission (define.xml, annotated CRFs, reviewer guides, transport files).
Collaborate with cross-functional stakeholders to communicate requirements, status, risks, and resource needs.
Develop ADaM specifications and support analyses with Biostatistics on endpoints and derivations.
Identify opportunities to improve processes and drive best practices.
Ensure data, analysis, CDISC, and regulatory submission standards are followed across studies.