NAMs Data Harmonization Specialist

NYU Langone Health; New York (NY); On-site; USD 84,577 - 126,991; Full time

Benefits offered by this job

Comprehensive benefits package

Generous time-off

Holistic wellness program

Job summary

NYU Langone Health is seeking a Data Science Analyst/Engineer to join their team in New York City. This role involves analyzing and developing specifications for NAMs data structures. The ideal candidate will have a Master's in a quantitative discipline and expertise in Python or R.

The position includes a comprehensive benefits package focusing on well-being and career development. Salary ranges from $84,577.93 to $126,991.52 annually. NYU Langone Health is committed to inclusion and equal opportunity.

Qualifications

• Masters degree in a quantitative field and 3 years of experience in machine learning/data science.
• Proficiency in at least one programming language (Python, R) and machine learning tools.
• Excellent written and oral communication skills.

Responsibilities

• Analyze source NAMs datasets to characterize data structure and quality.
• Develop source-to-CDM mapping specifications, including transformation rules.
• Author functional ETL requirements to guide pipeline development.

Skills

Proficiency in Python

Machine learning tools (scikit-learn, R)

Predictive modeling knowledge

Big data computing models

Databases knowledge (SQL, NoSQL)

Software engineering principles

Education

Masters degree in a quantitative discipline

Tools

Hadoop

Apache Spark

Python

R

Job description

NYU Langone Health is seeking a Data Science Analyst/Engineer to join their team in New York City. This role involves analyzing and developing specifications for NAMs data structures. The ideal candidate will have a Master's in a quantitative discipline and expertise in Python or R.

The position includes a comprehensive benefits package focusing on well-being and career development. Salary ranges from $84,577.93 to $126,991.52 annually. NYU Langone Health is committed to inclusion and equal opportunity.