Data Science, Emerging Talent Intern

Job Description

Data Science, Emerging Talent Intern | MTA

The Tone:
This is an internship at MTA, located onsite in New York, NY. The MTA’s Data & Analytics team is responsible for building and operating the organization’s core data infrastructure. This role directly contributes to developing internal and public-facing data products and provides crucial support for executive decision-making on the MTA’s highest-impact initiatives. The intern will help manage data pipelines and conduct advanced analyses that cover critical areas such as ridership, operations, and revenue.

The TL;DR
• Role: Internship
• Location: New York, NY
• Pay: $19–$21 hourly
• Team: MTA Data & Analytics Team
• Mission: This person helps build and maintain the MTA’s core data infrastructure and provides critical analytical insights to support executive decision-making.
• Tech Stack: SQL, Spark, Python, Apache Airflow, Power BI, Mode Analytics, Excel, Tableau, Microsoft Office Suite

What You’ll Actually Do
• Data Transformation: Write and maintain code to clean, combine, and transform large operational datasets, ensuring data quality for analysis.
• Data Analysis: Conduct in-depth exploratory and structured analyses to address key questions and provide insights to MTA leadership.
• Pipeline Management: Monitor, validate, and enhance production data pipelines for accuracy, reliability, and maintainability, specifically utilizing Apache Airflow.
• Data Visualization: Build informative dashboards using tools like Power BI and Mode Analytics to visualize data and provide actionable insights for stakeholders.
• Communication: Author presentations and comprehensive written documentation to clearly communicate findings to both technical and non-technical audiences.

The Must-Haves
• Background: An emerging talent intern must be a matriculated undergraduate student (minimum GPA 2.5) or graduate student (minimum GPA 2.8) in Computer Science, Data Science, Transportation, Urban Science and Informatics, Economics, Statistics, or a related field.
• Experience: Strong experience in Python or SQL coding is required, along with experience using analytical tools such as Excel, Power BI, Tableau, or Mode Analytics. Candidates should also have experience in coding, documenting processes, and performing data quality checks.
• Skills: Strong data analytic skills are essential, including a solid understanding of analytical methods like probability and statistics and algorithm design. Candidates must possess excellent organizational, analytical, and communication skills, and demonstrate the ability to work effectively under pressure, prioritize tasks, and contribute as an active team player.
• Bonus: Knowledge of and preferably some experience in data engineering, with experience in Apache Airflow being particularly valuable.