Overview

The Ridership Analysis and Modeling unit inside the Division of Operations Planning taps into vast and diverse datasets to develop insights into ridership patterns as well as performance trends across the bus and subway networks. Our algorithms and analyses deliver insights to planners, schedulers, and leadership across NYCT. Projects include developing in-house ridership models to analyze ridership trends, utilizing transportation software such as TransCAD to forecast ridership under different scenarios, and developing processes and reports to effectively share this data. Our work also includes exploring newly available ridership and performance data sources to develop new data pipelines and improve existing analytical tools. Insights from our analyses inform all scales of planning for New York City’s transit system, including schedule writing, service diversions, network redesigns, and large-scale capital projects.

This position may include validating new datasets, engineering backend data flows, designing visualizations for internal and external use, updating processes for modeling and measuring ridership, updating passenger-perspective performance metrics calculation, exploring new data collection technologies, and developing algorithms that integrate multiple data sources to produce actionable insights. These projects may involve data sources such as Automated Fare Card (AFC) records, Automated Passenger Counts (APC), anonymized mobile device data as well as bus and subway movement data. Specific tasks may include analyzing data using SQL and Excel, automating processes in Python or Java, designing reports to disseminate findings, and writing associated documentation.

Education and Experience

Associate Staff Analyst

1. A Master’s degree from an accredited college with a major in transportation science, civil engineering, data science, computer science, information technology, urban planning, mathematics, geography, economics, business or public administration, management science, operations research, statistics, urban studies or a closely related field; and ONE(1) year of satisfactory full-time professional experience in one or a combination of the following: data analytics, transportation planning, public administration, fiscal or economic research, operations research, or in a related field; OR

2. A Baccalaureate degree from an accredited college and THREE (3) years of satisfactory full-time professional experience in the areas described in 1 above.

Staff Analyst I & Staff Analyst II

1. A Master’s degree from an accredited college with a major in transportation science, civil engineering, data science, computer science, information technology, urban planning, mathematics, geography, economics, business or public administration, management science, operations research, statistics, urban studies or a closely related field; OR

2. A Baccalaureate degree from an accredited college and TWO (2) years of satisfactory full-time professional experience working in one or a combination of the following areas: data analytics, transportation planning, public administration, fiscal or economic research, operations research or in a related area.

Special Note:

To be eligible for placement in Assignment Level II, individuals must have, after meeting the minimum requirements, one additional year of professional experience as described in “2” above

Staff Analyst Trainee I

1. A Baccalaureate degree from an accredited college.

Staff Analyst Trainee II

1. Completion of 1 year of satisfactory experience as Staff Analyst Trainee I.

All candidates must possess a baccalaureate degree in order to apply to this position.

Desired Skills

The ideal candidate will have a combination of analytical, technical, planning, and communication skills, preferably among the following areas:

· Proficient in standard analytical data processing and management support tools including office productivity suites, including advanced Excel analysis.

· Understanding of analytical methods (e.g. probability and statistics, and algorithm design, particularly for ridership modeling and analysis).

· Experience developing creative visualizations of large datasets.

· Experience with relational databases (e.g. Oracle, Postgres, Access), including writing queries (generally with PL/SQL) to obtain and manipulate large data sets.

· Experience programming for data analytics, most preferably in Python, but other languages such as R and Java are valuable.

· Familiarity with transit/transportation systems, particularly the NYCT subway and bus network.

· Familiarity with transportation modeling software, such as TransCAD, Cube Voyager, or Emme.

· Familiarity with performance metrics and dashboards/scorecards, particularly in the transportation industry.

· Familiarity with transportation planning theory and practice, especially in large scale transit systems.

· Excellent writing, communication, and presentation skills

Selection Method

Based on evaluation of education, skills, experience and interview.

All selected candidates will be subject to a full background investigation that includes employment and education. Discrepancies may lead to dismissal.

Appointment may be at a comparable level to current level of selected candidate (if necessary).

Other Information

As an employee of NYCT or MABSTOA, you may be required to complete an annual financial disclosure statement with the State of New York, if your position earns more than $99,394 (this figure is subject to change) per year or if the position is designated as a policy maker.