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About This Role
Machine Learning & Data Engineer, Bureau of Data Technology & Strategy
- DEPT OF HEALTH/MENTAL HYGIENE
Posted on
09/30/2026
- Full-time
Location
QUEENS
- No exam required
Department
Data Tech & Strategy
Salary range: $109,565.00 – $135,000.00 Save
Job Description
The Center for Population Health Data Science (CPHDS) launched in October of 2023- aims to catalyze critical data modernization work and enable the agency to make progress toward linking public health, healthcare, and social service data for timely and effective public action. We are working towards making these data more accessible, equitable, meaningfully usable, and protected – and actively used to protect and promote the health and wellbeing of New Yorkers. We aim to strengthen agency wide data capabilities by empowering our workforce, enhancing intra- and inter-agency data sharing, and using modern technology to yield trusted and integrated data and insights. A real-time and comprehensive view of city needs is needed to enhance public health actions and improve health outcomes for the most vulnerable New Yorkers.
DUTIES WILL INCLUDE BUT NOT BE LIMITED TO:
- Support the development of integrated data pipelines that facilitates efficient data exchange, analysis, surveillance, and reporting.
-Collaborate with public health data stewards to understand data requirements for health informatics, integrating public health data standards and practices into our integrated data architecture. -Develop, and maintain scalable, secure data pipelines and platform to support real-time and batch data ingestion and processing from diverse internal and external data sources.
- Guide the selection and implementation of cutting-edge data technologies and tools to enhance our analytics and data science capabilities.
- Promote data governance, quality, and security best practices, ensuring compliance with applicable regulations and standards.
- Collaborate with internal and external stakeholders to align data infrastructure enhancements with the needs of diverse units.
PREFERRED SKILLS:
- Planning and project management skills with ability to adapt with new information and needs.
- Experience modeling population-level health outcomes, infectious disease transmission, behavioral dynamics, or health systems operations.
- Experience working with structured and unstructured datasets, including data from NYC or other municipal contexts.
- Knowledge of statistical inference, uncertainty quantification, sensitivity analysis, and validation techniques for simulation models.
- Prioritization and time management skills.
- Interpersonal and communications skills with ability to manage working relationships with individuals at all levels.
- High degree of self-awareness, humility, and diplomacy.
- 4 or more years of experience in data engineering, building and managing scalable data pipelines.
- Experience with cloud-based data solutions (e.g., Azure, AWS, or GCP), programming (e.g., Python, R), Linux systems, and big data technologies (e.g., Hadoop, Spark).
- Familiarity with health informatics, public health data standards (HL7, FHIR), and understanding of the unique needs in managing health-related data.
- Experience developing simulation modeling (e.g., agent-based models, discrete event simulations, system dynamic models).
- Experience identifying and integrating datasets for use in simulation or predictive modeling.
- Ability to translate modeling outputs into clear, actionable insights for stakeholders.
- Experience conducting scenario analysis to inform policy or program decision-making.
- Ability to mentor more junior staff, manage projects, and collaborate across diverse functional teams.
- Strong problem-solving and communication skills to effectively convey technical concepts to a broad audience.
Why you should work for us:
- Loan Forgiveness: As a prospective employee of the City of New York, you may be eligible for federal/state loan forgiveness and repayment assistance programs that lessen your payments or even fully forgive your full balance. For more information, please visit the U.S. Department of Education’s website (https://studentaid.gov/pslf/)
- Benefits: City employees are entitled to unmatched benefits such as:
o a premium-free health insurance plan that saves employees over $10K annually, per a 2024 assessment.
o additional health, fitness, and financial benefits may be available based on the position’s associated union/benefit fund.
o a public sector defined benefit pension plan with steady monthly payments in retirement.
o a tax-deferred savings program and
o a robust Worksite Wellness Program that offers resources and opportunities to keep you healthy while serving New Yorkers.
- Work From Home Policy: Depending on your position, you may be able to work up to two days during the week from home.
- Job Security - you could enjoy more job security compared to private sector employment and be able to contribute to making NYC a healthy place to live and work.
Established in 1805, the New York City Department of Health and Mental Hygiene (NYC Health Department) is the oldest and largest health department in the U.S., dedicated to protecting and improving the health of NYC. Our mission is to safeguard the health of every resident and cultivate a city where everyone, regardless of age, background, or location, can achieve their optimal health. We provide a wide array of programs and services focused on food and nutrition, anti-tobacco support, chronic disease prevention, HIV/AIDS treatment, family and child health, environmental health, mental health, and social justice initiatives. As the primary population health strategist and policy authority for NYC, with a rich history of public health initiatives and scientific advancements, from addressing the 1822 yellow fever outbreak to the COVID-19 pandemic, we serve as a global leader in public health innovation and expertise.
Come join us and help to continue our efforts in making a difference in the lives of all New Yorkers!
Commitment to Equity:
The City of New York is an inclusive equal opportunity employer committed to recruiting and retaining a diverse workforce and providing a work environment that is free from discrimination and harassment based upon any legally protected status or protected characteristic, including but not limited to an individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, veteran status, gender identity, or pregnancy.
The NYC Health Department is an inclusive equal opportunity employer committed to providing access and reasonable accommodation to all individuals. To request reasonable accommodation to participate in the job application or interview process, contact Sye-Eun Ahn, Director of the Office of Equal Employment Opportunity, at [email protected] or 347-396-6549.
CITY RESEARCH SCIENTIST - 21744
Minimum Qualifications
- For Assignment Level I (only physical, biological and environmental sciences and public health) A master's degree from an accredited college or university with a specialization in an appropriate field of physical, biological or environmental science or in public health.
To be appointed to Assignment Level II and above, candidates must have:
- A doctorate degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and one year of full-time experience in a responsible supervisory, administrative or research capacity in the appropriate field of specialization; or
- A master's degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and three years of responsible full-time research experience in the appropriate field of specialization; or
- Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least a master's degree in an appropriate field of specialization and at least two years of experience described in "2" above. Two years as a City Research Scientist Level I can be substituted for the experience required in "1" and "2" above.
NOTE:
Probationary Period
Appointments to this position are subject to a minimum probationary period of one year.
Public Service Loan Forgiveness
As a prospective employee of the City of New York, you may be eligible for federal loan forgiveness programs and state repayment assistance programs. For more information, please visit the U.S. Department of Education’s website at https://studentaid.gov/pslf/.
Residency Requirement
New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.
Additional Information
The City of New York is an inclusive equal opportunity employer committed to recruiting and retaining a diverse workforce and providing a work environment that is free from discrimination and harassment based upon any legally protected status or protected characteristic, including but not limited to an individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, veteran status, gender identity, or pregnancy.
Apply Save
Job ID
803214
Posted until
11/29/2026
Title code
21744
Civil service title
CITY RESEARCH SCIENTIST
Title classification
Non-Competitive-5
Business title
Machine Learning & Data Engineer, Bureau of Data Technology & Strategy
- Experience level: Experienced (non-manager)
Job level
4A
Number of positions
1
Work location
42-09 28th Street
- Category: Technology, Data & Innovation
Machine Learning & Data Engineer, Bureau of Data Technology & Strategy
Salary Context
This $109K-$135K range is below the median for Data Engineer roles in our dataset (median: $151K across 28 roles with salary data).
Role Details
About This Role
Data Engineers build the pipelines that feed AI models. They design ETL workflows, manage data lakes, and ensure training and inference data is clean, timely, and accessible. Without good data engineering, AI projects fail. It's that simple.
The AI era has expanded the data engineer's scope far beyond batch ETL jobs. You're building real-time embedding pipelines for RAG systems, managing vector databases, ensuring training data quality at scale, and building the infrastructure that lets ML teams iterate on data as fast as they iterate on models. Data quality is the biggest predictor of model quality, and you're the person responsible for it.
Across the 9,653 AI roles we're tracking, Data Engineer positions make up 1% of the market. At New York City Department of Health and Mental Hygiene, this role fits into their broader AI and engineering organization.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
What the Work Looks Like
A typical week includes: debugging a data pipeline that's producing stale embeddings for the RAG system, optimizing a Spark job that processes training data, building a data quality monitoring dashboard, meeting with the ML team to understand their next data requirements, and writing dbt models that transform raw event data into ML-ready features. The work is deeply technical and high-impact.
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
Skills Required
SQL, Python, and distributed systems (Spark, Airflow, dbt) are core. Cloud data platforms (Snowflake, BigQuery, Redshift) are increasingly standard. Many AI-focused roles also want familiarity with vector databases and embedding pipelines. Understanding data modeling, pipeline orchestration, and data quality frameworks covers the essentials.
AI-specific data engineering skills include: building feature stores, managing training data versioning, implementing data lineage tracking, and building real-time embedding pipelines. Experience with streaming systems (Kafka, Flink) is valuable for real-time AI applications. Understanding ML data requirements (balanced datasets, data augmentation, evaluation set construction) makes you much more effective working with ML teams.
Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
Compensation Benchmarks
Data Engineer roles pay a median of $177,825 based on 160 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($122K) sits 31% below the category median. Disclosed range: $109K to $135K.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
New York City Department of Health and Mental Hygiene AI Hiring
New York City Department of Health and Mental Hygiene has 1 open AI role right now. They're hiring across Data Engineer. Based in Queens, NY, US. Compensation range: $135K - $135K.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Data Engineer roles include Backend Engineer, Database Administrator, Analytics Engineer.
From here, career progression typically leads toward Senior Data Engineer, ML Engineer, Data Platform Lead.
Master SQL and Python first. Then learn a distributed processing framework (Spark or its modern alternatives) and a pipeline orchestrator (Airflow, Dagster, Prefect). Build a portfolio project that demonstrates end-to-end pipeline construction: ingest, transform, validate, serve. If you want to specialize in AI data engineering, add vector databases and embedding pipelines to your skill set.
What to Expect in Interviews
Expect SQL deep-dives (query optimization, partitioning strategies, data modeling), Python coding focused on data pipeline patterns, and system design questions about building scalable ETL workflows. Companies with ML teams will ask about feature stores, embedding pipelines, and training data management. Be ready to discuss data quality monitoring, pipeline orchestration, and how you'd handle schema evolution in a production data lake.
When evaluating opportunities: Strong postings specify the data stack, mention ML pipeline work, and describe the scale of data you'll be working with. Look for companies that understand the connection between data quality and model quality. Avoid roles that conflate data engineering with data analysis.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Data Engineer demand in AI contexts is strong and growing. Every company building AI needs clean, reliable data pipelines. The shift toward real-time AI applications (chatbots, recommendation engines, agent systems) means data engineering is more critical than ever. Companies are willing to pay premium salaries for data engineers with AI/ML pipeline experience.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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