Senior Data Analyst - Onsite in Manhattan, Biostatistics

NYU Langone Health; New York (NY); On-site; USD 70,000 - 93,000; Full time

Job summary

NYU Langone Health invites applications for a Senior Data Analyst within the Optimal Aging Institute. The role focuses on high-impact epidemiologic research on Alzheimer’s disease and cognitive aging, applying advanced statistical methods to large longitudinal cohorts.

The successful candidate will work with investigators on study design, data preparation, analyses, and manuscript preparation, mentoring team members in R, SAS, Stata, and Mplus.

Qualifications

• Master's degree in a relevant field such as public health, epidemiology, biostatistics, data science, or related discipline.
• At least 2 years of relevant experience conducting data analysis in healthcare/public health settings.
• Advanced proficiency in statistical methods for longitudinal/multivariate data, survival analysis, and high-dimensional data; strong computational skills in SQL, SAS, R, or Stata.
• Ability to manage multiple analytic workstreams, collaborate, and communicate effectively.

Responsibilities

• Design study protocols, develop data procedures, prepare data, run statistical analyses, and interpret results.
• Write statistical reports for manuscripts and studies; present at seminars and conferences.
• Train team members in R, SAS, Stata, or Mplus; provide methodological guidance.
• Collaborate with epidemiology, biostatistics, and medical researchers on study design and grant work.
• Ensure reproducibility with documentation and version control; develop data visualizations.

Skills

SQL

R

SAS

Stata

Mplus

Epidemiology

Biostatistics

Study design

Education

Master's degree in public health/epidemiology/biostatistics/data science

Tools

SQL

SAS

R

Stata

Mplus

Job description

NYU Langone Health invites applications for a Senior Data Analyst within the Optimal Aging Institute. The role focuses on high-impact epidemiologic research on Alzheimer’s disease and cognitive aging, applying advanced statistical methods to large longitudinal cohorts.

The successful candidate will work with investigators on study design, data preparation, analyses, and manuscript preparation, mentoring team members in R, SAS, Stata, and Mplus.