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About This Role
Data Scientist
- DEPARTMENT OF TRANSPORTATION
Posted on
09/23/2026
- Full-time
Location
MANHATTAN
- No exam required
Department
Franchise/Concessions/Consents
Salary range: $87,743.00 – $110,120.00 Save
Job Description
The New York City Department of Transportation (DOT) provides for the safe, efficient, and environmentally responsible movement of people and goods in the City of New York and maintains and enhances the transportation infrastructure crucial to the economic vitality and quality of life of City residents. DOT is an equal opportunity employer, committed to recruiting and maintaining a diverse workforce in an open and inclusive environment.
This candidate will serve as a Data Scientist in NYC DOT’s Bike Share & Shared Mobility unit, which is responsible for planning and oversight of the Citi Bike program and other shared micro mobility services in New York City. Citi Bike is a public transportation service and a public-private partnership that is among the largest and most successful bike share systems in the world. The program is in the midst of a five-year expansion that will ultimately double the size of its previous service area and put more than 40,000 bicycles within a five-minute walk of half of NYC residents. Other shared micro-mobility services in NYC include dockless e-scooter and e-moped shares.
We are seeking a visionary and analytical Data Scientist to join our team at a historic turning point as the original Bike Share Program Agreement nears its end in 2029 and the City prepares to reimagine the future of the bike share program. The position will serve as a core technical architect for what comes next. Beyond day-to-day system analytics, the position will research cutting-edge technology, evaluate back-end architecture, and craft technical requirements to support the future of bike share in NYC.
The position plays a pivotal role in shaping how we understand, monitor, and optimize our shared mobility systems. This individual will combine data science, advanced visualization, and strategic storytelling to translate complex data from Citi Bike and Shared E-Scooter programs into actionable insights that inform planning and day-to-day operations. The ideal candidate thrives at the intersection of analytics and communication - able to uncover patterns, craft compelling narratives, and partner with internal team members at all levels to drive informed decision-making.
Reporting to the Director of Data Science, the Data Scientist will be responsible for, but not limited to:
Data Analytics & Research
- Conduct research and analysis on bike share and shared mobility to inform current and future planning
- Develop predictive models to answer complex and nuanced questions about the programs and anticipate future needs and behavior of the systems (e.g., simulate how different pricing mechanisms impact ridership and system revenue)
- Prepare reports and briefing materials based on the databases that underlie the bike share and shared mobility systems
- Monitor vendor compliance with governmental regulations, DOT policies, and contract terms
- Respond quickly and accurately to ad hoc data requests for internal and external stakeholders
Visualization & Storytelling
- Develop and maintain dashboards to deliver insights to internal team members using software such as Power BI
- Translate data into stories that resonate with senior staff, managers, and staff, highlighting both the "what" and the "why"
Strategic Thinking & Partnership
- Research and evaluate best practices for bike share technology, hardware, and data infrastructure to support leadership in crafting technical specifications for the future of bike share in NYC
- Collaborate with leadership, Operations, Planning, and Policy teams to align analytics and research agendas with organizational priorities
- Offer evidence-based recommendations to support system planning, managing existing service areas, and shaping future policy decisions
- Act as a trusted advisor and build strong relationships with the internal team members.
Data Management
- Monitor data quality, identify issues, and maintain data integrity.
- Document data management procedures (e.g., data dictionaries, business rules)
- Plan, design, maintain, and support unit internal databases
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.
Preferred Skills
- Mastery with spreadsheets and at least one coding language (Python, R, etc.) for data manipulation - Experience in querying, cleaning, and maintaining large relational databases using SQL - Experience with data visualization software such as Power BI and/or Tableau - Strong familiarity with providing statistical support by participating in the development of statistical methodology, study design, and data analysis of analytical projects - Mastery with presentation slides, data visualization software, maps, and memos. This includes leveraging visualization tools to present information in a way that drives fact-based decision making by developing intuitive static and interactive data graphics - Ability to relate complex trends in the data to larger policy issues, to work with the operations and planning team to tailor data analysis and products to their needs -Excellent interpersonal, analytical, research, presentation, written, and oral communication skills -Willingness to be flexible and work as part of a team -Experience or interest in transportation planning, logistics, bike share, micro mobility, cycling, and working with or in the public sector.
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
801078
Posted until
11/22/2026
Title code
21744
Civil service title
CITY RESEARCH SCIENTIST
Title classification
Non-Competitive-5
Business title
Data Scientist
- Experience level: Experienced (non-manager)
Job level
02
Number of positions
1
Work location
55 Water St Ny Ny
- Category: Public Safety, Inspections, & Enforcement
Data Scientist
Salary Context
This $87K-$110K range is in the lower quartile for Data Scientist roles in our dataset (median: $167K across 150 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 8,943 AI roles we're tracking, Data Scientist positions make up 4% 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 $190,000 based on 1,406 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($98K) sits 48% below the category median. Disclosed range: $87K to $110K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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: $272,250; VP: $235,000.
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 Manhattan, NY, US. Compensation range: $110K - $110K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. 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 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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