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About This Role
Program Data Scientist
==========================
- DEPARTMENT OF TRANSPORTATION
Posted on
08/03/2026
- Full\-time
Location
NYC\-ALL BOROS
- No exam required
Department
Tf. Eng./Elect Shop
Salary range: $109,565\.00 – $142,112\.00
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Job Description
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The Program Data Scientist designs and leads the analytics behind the Division of Traffic Operations’ traffic signal capital program building the data systems, methods, and analyses that make a large, fast\-moving portfolio of projects visible, understandable, and actionable. Working as a peer to the program’s delivery manager, this role turns project, contract, and asset data into the insight that keeps signal infrastructure moving from design completion to final acceptance and keeps the streets that depend on it working. The Program Data Scientist will support the NYC Streets Plan by turning project and contract data into actionable insight that ensures signal installations advance transit priority corridors, Better Buses projects, and other transit supportive street improvements.
This is an applied research role with wide latitude to define the analytical approach: what to measure across hundreds of concurrent projects and multiple contractors, how to structure the data, and how to present it so decision\-makers can act quickly. The strongest candidates are fluent in Python and GIS, rigorous about data quality, and able to translate complex analysis for non\-technical audiences. As the program’s first dedicated analyst, you’ll shape from the ground up how data serves the delivery of public infrastructure.
About NYC DOT and the Division of Traffic Operations
NYC DOT works to support the safe, equitable, and sustainable movement of people and goods across New York City. Within NYC DOT, the Division of Traffic Operations delivers and sustains the systems that help New Yorkers and visitors move safely and efficiently every day.
Traffic Operations manages the infrastructure that keeps New York City’s streets working including more than 350,000 streetlights, approximately 14,000 signalized intersections, roughly 90,000 on\-street parking spaces, over 4,000 automated enforcement cameras, and a state\-of\-the\-art Traffic Management Center. The division plans, builds, operates, and maintains the traffic signals that millions of New Yorkers depend on every day.
Transit Development (TD) is responsible for developing public transit\-supportive street infrastructure and policies in order to improve mobility for all New Yorkers. The unit manages the bus\-related components of the NYC Streets Plan, including the Better Buses and transit policy initiatives, and develops location\-specific projects to help the quality and safety of bus operations and to improve pedestrian access to transit. TD also serves as a resource to the agency on public transit\-related matters, including acting as one of the key points of contact with the Metropolitan Transportation Authority (MTA).
Responsibilities
- Design and develop analytical systems that track a large portfolio of signal projects simultaneously across stages of work, contracts, and contractors so the full program is visible in one place and every project stays accounted for.
- Build and maintain data pipelines and analytical tools that ingest, clean, and join project, contract, and asset data from across the division.
- Apply GIS methods to analyze and map the program’s geographically distributed infrastructure, connecting delivery data to the intersections New Yorkers move through every day.
- Develop the metrics and analyses that reveal how projects move through delivery surfacing trends, bottlenecks, and risks early enough to keep the program on pace.
- Evaluate data quality and analytical methods across the program, and coordinate with units across the division to improve how delivery data is captured and used.
- Present findings and recommendations to division leadership, translating complex analysis into clear direction for a program that reaches every corner of the city.
Division: Traffic Operations
Unit: Finance, Contracts and Innovation Unit
Location: 34\-02 Queens Blvd. LIC, NY 11101
Hours and Shift: 35 HRS/Mon\-Fri/9am\-5pm
Preferred Skills:
Successful candidates often demonstrate the following, though not every qualification is required:
- Strong proficiency in Python for data analysis, pipeline building, and automation.
- Experience with GIS tools and spatial analysis (e.g., ArcGIS, QGIS, geospatial Python libraries).
- Experience designing analyses or data systems for tracking capital projects, infrastructure, or other complex operational programs.
- Ability to communicate analytical findings clearly to non\-technical and executive audiences.
*
We recognize that strong candidates may come from a variety of backgrounds and experiences. If this position interests you and you meet many but not all of the criteria, we encourage you to apply.
To Apply:
All resumes are to be submitted electronically using one of the following methods:
Please go to www.nyc.gov/careers/search and search for the JOB ID \#: 785892
Current employees please log on into Employee Self Service at https://hrb.nycaps.nycnet and follow the Careers Link for JOB ID \#: 785892
No phone calls, faxes or personal inquiries permitted.
Only applicants under consideration will be contacted.
Most public libraries have computers available for use.
Note: New hires must reside in NYC for the first two years of employment. Appointments are subject to OMB approval.
For more information about DOT, visit us at: www.nyc.gov/dot.
Additional Information:
Note: This position is open to qualified persons with a disability who are eligible for the 55\-a program. Please indicate in your resume or cover letter that you would like to be considered for the position under the 55\-a program.
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 StudentAid.gov/PSLF.
This position may be eligible for remote work up to 2 days per week, pursuant to the Remote Work Pilot Program agreed to between the City and DC37\.
CITY RESEARCH SCIENTIST \- 21744
Minimum Qualifications
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1\. 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:
1\. 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
2\. 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
3\. 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.
Preferred Skills
--------------------
Successful candidate should demonstrate the following, though not every qualification is required: \- Strong proficiency in Python for data analysis, pipeline building, and automation. \- Experience with GIS tools and spatial analysis (e.g., ArcGIS, QGIS, geospatial Python libraries). \- Experience designing analyses or data systems for tracking capital projects, infrastructure, or other complex operational programs. \- Ability to communicate analytical findings clearly to non\-technical and executive audiences. \- We recognize that strong candidates may come from a variety of backgrounds and experiences. If this position interests you and you meet many but not all of the criteria, we encourage you to apply.
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
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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
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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
785892
Posted until
10/02/2026
Title code
21744
Civil service title
CITY RESEARCH SCIENTIST
Title classification
Non\-Competitive\-5
Business title
Program Data Scientist
- Experience level: Experienced (non\-manager)
Job level
4A
Number of positions
1
Work location
34\-02 Queens Boulevard Long Is
- Category: Administration \& Human Resources
Program Data Scientist
Salary Context
This $109K-$142K range is in the lower quartile for Data Scientist roles in our dataset (median: $160K across 258 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 4,317 AI roles we're tracking, Data Scientist positions make up 8% of the market. At New York City Department of Transportation, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 789 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($125K) sits 35% below the category median. Disclosed range: $109K to $142K.
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 Transportation AI Hiring
New York City Department of Transportation has 1 open AI role right now. They're hiring across Data Scientist. Based in New York, NY, US. Compensation range: $142K - $142K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
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).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
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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