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Internship Transportation Data Scientist Jobs in Pennsylvania

RELX Group plc

Data Scientist III

Philadelphia, PA · On-site

$110.49K - $115.60K/yr

Lead the Rising Tide program and Mentor interns. Coordinate with IT developers and (content) subject matters experts to translate information needs into data science solutions. Drive new developments ...

RELX

Data Scientist III

Philadelphia, PA · On-site +1

$110.49K - $115.60K/yr

Lead the Rising Tide program and Mentor interns. Coordinate with IT developers and (content) subject matters experts to translate information needs into data science solutions. Drive new developments ...

SynergisticIT

Data Engineer

Philadelphia, PA · On-site

$95K - $150K/yr

Internship or project experience in data science or data engineering Client Requirements Our U.S.-based clients typically require: * Real-world project experience : Hands-on exposure to enterprise ...

The Pennsylvania State University

$15/hr

Advance interns will work on AI-related projects in an Agile software development team ... Specifically, the Data Scientist will research state-of-the-art algorithms in machine learning to ...

Waabi

Applied Scientist

Pittsburgh, PA · On-site +1

$128K - $184K/yr

With a world-class team, we're unlocking the next era of autonomous transportation with technology ... We are looking for a hands-on Applied Data Scientist to help drive a unified view of our multi ...

Waabi

Applied Scientist

Pittsburgh, PA · On-site +1

$128K - $184K/yr

With a world-class team, we're unlocking the next era of autonomous transportation with technology ... We are looking for a hands-on Applied Data Scientist to help drive a unified view of our multi ...

Merck & Co.

$95.50K - $121.70K/yr

The Transporter Science Group serves as a center of excellence for the design, execution, and ... data in support of project teams across therapeutic areas. This individual should have strong ...

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Internship Transportation Data Scientist information

What are the key skills and qualifications needed to thrive as an Internship Transportation Data Scientist, and why are they important?

To thrive as an Internship Transportation Data Scientist, you need a solid grounding in statistics, data analysis, and programming, often supported by coursework or experience in transportation engineering, mathematics, or computer science. Familiarity with tools like Python, R, SQL, and GIS software, as well as exposure to data visualization platforms and relevant certifications, is highly valuable. Strong problem-solving abilities, attention to detail, and effective communication skills help you interpret complex data and present actionable insights to diverse stakeholders. These skills are essential for analyzing transportation systems, optimizing operations, and supporting evidence-based decision-making in the field.

What types of projects can an Internship Transportation Data Scientist expect to work on, and how do these contribute to larger organizational goals?

As an Internship Transportation Data Scientist, you may work on projects such as analyzing traffic patterns, optimizing public transit schedules, or developing predictive models for transportation demand. These projects typically involve cleaning and visualizing large datasets, running statistical analyses, and presenting actionable insights to stakeholders. Your work directly supports the organization by informing decision-making, improving efficiency, and contributing to safer, more sustainable transportation systems. You'll often collaborate with engineers, urban planners, and other data professionals, gaining exposure to interdisciplinary teamwork and real-world problem solving.

What are Internship Transportation Data Scientists?

Internship Transportation Data Scientists are students or recent graduates who assist in analyzing and interpreting transportation-related data to improve systems and operations. They work with large datasets from sources like traffic sensors, GPS, or public transit, using statistical and machine learning techniques to extract insights. Their tasks often include data cleaning, visualization, model development, and reporting findings to support transportation planning and policy. This role provides hands-on experience in applying data science to solve real-world transportation challenges.
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Senior Data Scientist

Perpay - Career's Page

Philadelphia, PA

Other

Posted 14 days ago

Job description

About the Role:

As a Senior Data Scientist at Perpay, you will be a critical player in the day-to-day success of the business, supporting new and existing product initiatives through strong analytical skills and machine learning expertise. In addition, you will be responsible for helping shape the future of the data science team by developing processes and systems that scale with our rapidly growing business. This is an exciting opportunity to make a positive impact on the execution of Perpay's mission and the lives of our customers. We are looking for someone who is passionate about all aspects of data science: from machine learning and exploratory data analysis to communication of results and real-time deployments. This crucial role will sit on our data science team and report to the Data Science Manager. If you're looking for a collaborative team that you can bounce ideas off of and learn from, this is where you belong. We are about being curious, setting the standard and building good habits at Perpay.

Our greatest strength is our people and we'd love for you to be one of them!

Responsibilities:
  • Drive the end-to-end completion of data science initiatives, collaborating with stakeholders from ideation through execution, ensuring projects deliver strong impact to our customer's financial lives and the health of the business
  • Proactively identify opportunities for the data science team to improve and expand Perpay's business model using techniques from exploratory data analysis to machine learning models, leveraging subject matter expertise of Perpay's business model
  • Support the growth of the business by delivering scalable models and algorithms while maintaining and troubleshooting existing resources
  • Deploy and maintain real-time model inference resources and infrastructure
  • Deploy and maintain machine learning pipelines including batch processing and continuous training architecture
  • Contribute to the cross-discipline adoption and responsible use of AI/LLM models and services at Perpay 
  • Present results and analyses to the a wide range of audiences: from Perpay's leadership team to non-technical peers
  • Contribute to defining standards and best practices concerning workflow and adoption of new technologies within the Data Science team
  • Act as an informal mentor peers
What You'll Bring:
  • 5+ years of experience* and expertise applying machine learning techniques in industry
  • 5+ years of experience* and expertise in producing data analysis, exploratory data analysis and data visualization in industry
  • 5+ years of experience* and expertise in developing, deploying, maintaining real-time software (e.g. models exposed as APIs)
  • 5+ years of experience* and expertise in Cloud compute infrastructure and best practices, including familiarity with tools such as terraform and Cloud Formation
  • Bachelor's degree or higher in a quantitative/technical field (Mathematics, Statistics, Engineering, Chemistry, Physics)
  • Excellent communication skills, across a range of audiences from technical to non-technical
  • Strong business acumen, demonstrated through subject matter expertise in at least one industry
  • Capable of managing projects "end to end" including managing project scope, timelines and workloads
  • Advanced proficiency in Python and standard data science stack (e.g. scikit-learn, pandas, numpy, matplotlib, etc.)
  • Team player: willingness and ability to establish strong working relationships not just within the data science team itself, but across the organization

*Internships not included

Nice to have:
  • Expertise in multiple advanced machine learning methodologies: e.g. deep learning, probabilistic programming, mathematical optimization, etc.
  • Deep familiarity in multiple advanced machine learning frameworks: e.g. tensorflow, pytorch, pymc, etc.
  • Experience with scalable compute frameworks such as Spark or Polars
  • Experience with deployment frameworks such as Kubernetes

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