Director, Clinical Statistics

  • CHDI Foundation
  • Princeton, NJ
  • Sep 08, 2020
Full time Nonprofit-Social Services Pharmaceutical Research Science

Job Description

Director, Clinical Statistics, Princeton, New Jersey


Job Location

The position will be based in Princeton, N.J. with occasional travel to CHDI’s other offices in LA and NYC.


CHDI Foundation, Inc.

CHDI is a private, not-for-profit research organization. We work with an international network of scientists to discover drugs that slow the progression of Huntington’s disease (HD). We seek to accelerate scientific progress by serving as a collaborative enabler. Our strategy is to encourage researchers to develop practical ideas, useful research materials, and powerful technologies, often by providing financial support. Our activities extend from exploratory biology to the identification and validation of therapeutic targets, and from drug discovery and development to clinical studies and trials.


Director, Clinical Statistics

This position will report to a Vice President/Unit Leader and will be responsible for coordinating internal and external statistical modeling projects in HD.


Job responsibilities

  • Manage a portfolio of internal and external statistical modeling collaborations in support of CHDI’s clinical development efforts.
  • Contribute to ongoing scientific dialog around the planning and execution of statistical and modeling efforts within the Foundation.
  • Clean, manage and analyze data and communicate results as needed. Professional qualifications/skills
  • The ideal candidate will
  • Have an advanced degree (Phd) in statistics, data science, biostatistics, epidemiology, public health, biomedical informatics, bioinformatics or related fields and a strong interest in healthcare or biological research.
  • Demonstrate the ability to
    • Creatively apply statistical and/or data mining techniques in the context of cross-sectional, longitudinal clinical study data. Techniques of interest include: regression, analysis of variance, mixed effects modeling, causal modeling, clustering, random forests, SVMs, text mining, etc.
    • Apply experimental design concepts to the planning of data mining, observational and interventional studies
    • Code and analyze data in a one or more standard programming/scripting languages (e.g. R, MATLAB, NONMEM, STATA, SAS, Python, Perl, Stan)
    • Learn new statistical/data mining techniques and programming languages as needed.
    • Interpret methodological results and convey them to a non-technical audience in an easy and effective manner.
    • Manage and clean data. Personal skills:
  • Demonstrated skill in prioritization and time management.
  • Demonstrated ability to organize, initiate and work independently to address responsibilities
  • Team oriented with excellent interpersonal skills
  • Excellent oral and written communication skills. Please send resumes to