Remote-Eligible ML & Data Engineer for Public Health Data

ASPBP; New York (NY); Hybrid; USD 125,000 - 150,000; Full time

Benefits offered by this job

Health insurance

Pension plan

Work From Home policy

Loan forgiveness program

Job summary

The City of New York's Center for Population Health Data Science seeks a skilled City Research Scientist to advance data modernization, build scalable pipelines, and enable real-time analytics for public health decision-making.

Responsibilities include developing data infrastructure, guiding technology choices, and ensuring governance, security, and compliance across diverse data sources and stakeholders.

Qualifications

• Master's degree in an appropriate field of physical, biological, environmental science or public health.
• Doctorate or master’s with required experience for higher levels per NYC rules.
• Two years supervisory, administrative or research experience; or equivalent.
• Two years as City Research Scientist Level I can be substituted for some experience.

Responsibilities

• Support the development of integrated data pipelines for exchange, analysis, surveillance, and reporting.
• Collaborate with data stewards to understand data requirements and integrate health informatics standards.
• Develop and maintain scalable data pipelines for real-time and batch ingestion and processing.

Skills

Planning & PM

Health modeling

Data wrangling

Statistics

Prioritization

Communication

Professionalism

Data engineering

Cloud platforms

Health IT standards

Simulation modeling

Dataset integration

Visualization

Scenario analysis

Mentorship

Problem solving

Education

Master's degree in public health/related field

Doctoral degree in relevant field

Tools

Python

R

Azure

AWS

GCP

Linux

Hadoop

Spark

Job description

The City of New York's Center for Population Health Data Science seeks a skilled City Research Scientist to advance data modernization, build scalable pipelines, and enable real-time analytics for public health decision-making.

Responsibilities include developing data infrastructure, guiding technology choices, and ensuring governance, security, and compliance across diverse data sources and stakeholders.