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About This Role
Director of Applied Data Science and Solutions, Bureau of Data Technology \& Strategy
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- DEPT OF HEALTH/MENTAL HYGIENE
Posted on
07/27/2026
- Full\-time
Location
QUEENS
- No exam required
Department
Data Tech \& Strategy
Salary range: $75,000\.00 – $140,000\.00
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Job Description
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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 for timely and effective publication. We are working towards making these data more accessible, timely, equitable, meaningfully usable, and protected – and actively used to protect and promote the health and wellbeing of New Yorkers. We aim to strengthen agencywide 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. The CPHDS is working to strengthen citywide population health surveillance by better linking public health, healthcare, and social service data to fully characterize and improve the health of New Yorkers. Our vision is for these data to be accessible, timely, equitable, meaningfully usable, and protected in order to protect and promote health and wellbeing of New Yorkers.
The Bureau of Data Technology and Strategy (DTS) is dedicated to the development of the Enterprise Data Platform (EDP) and is home to data strategy, data governance, data product management, data engineering, and data science capabilities. The Applied Data Science unit within DTS oversees a number of mission critical agency projects including the Master Patient Index project, the Client Engagement Platform project, the Whole Genome Sequencing project, and various interoperability projects to support Disease surveillance systems. The unit also provides analytical support for ad hoc analyses and admin support for the Enterprise Data Platform.
Duties will include but not be limited to:
- Lead and oversee all aspects of the Master Patient Index project and including the development of service endpoints, integrations with other systems, and building of entity resolution models.
- Provide management, design, and developer support for interoperability projects underlying critical surveillance systems, whole genome sequencing project, client engagement platform project, and other novel projects that arise.
- Carry out code reviews with project developers, diagramming sessions with IT, and presentations for stakeholders.
- Coordinate project work across developers, IT admins, and vendors.
- Act as lead or supporting sql developer, python developer, or data scientist for any project as directed by leadership.
Preferred Skills:
- 8 or more years of Python experience
- 10 or more years of SQL development experience
- 5 or more years of business intelligence experience
- 5 or more years of statistical modeling experience
- 3 or more years of machine learning modeling experience
- Functional presentation and communication skills
Why you should work for us:
- 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!
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\.
IT AUTOMATION AND MONITORING E \- 95712
Minimum Qualifications
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1\. A baccalaureate degree in computer science, engineering or a related field from an accredited college and four years of satisfactory full\-time experience related to IT automation engineering, monitoring engineering, management of infrastructure; or
2\. Eight years of satisfactory full\-time experience related to IT automation engineering, monitoring engineering, management of infrastructure;
3\. Education and/or experience which is equivalent to "1" or "2" above.
Public Service Loan Forgiveness
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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
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New York City Residency is not required for this position
Additional Information
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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.
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Job ID
788243
Posted until
09/25/2026
Title code
95712
Civil service title
IT AUTOMATION AND MONITORING E
Title classification
Non\-Competitive\-5
Business title
Director of Applied Data Science and Solutions, Bureau of Data Technology \& Strategy
- Experience level: Manager
Job level
00
Number of positions
1
Work location
42\-09 28th Street
- Category: Technology, Data \& Innovation
Director of Applied Data Science and Solutions, Bureau of Data Technology \& Strategy
Salary Context
This $75K-$140K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At New York City Department of Health and Mental Hygiene, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Director-level AI roles across all categories have a median of $274,554. This role's midpoint ($107K) sits 50% below the category median. Disclosed range: $75K to $140K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
New York City Department of Health and Mental Hygiene AI Hiring
New York City Department of Health and Mental Hygiene has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in Queens, NY, US. Compensation range: $95K - $140K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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