Internship Opportunity: Data Science and Research & Innovation Support Intern

Transportation Technology Center, Inc.-posted about 1 month ago
Full-time • Intern
Pueblo, CO
251-500 employees
Executive, Legislative, and Other General Government Support
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The projects' general objectives include supporting research by way of data collection to improve railway safety, performance, and efficiency. Projects supported may include, but are not limited to, Exploratory Data Analysis (EDA), Supervised Machine Learning (ML) Applications, Feature Importance, Rail Inspection, and Wheel & Axle Inspection Technology. These projects may be funded by the Association of American Railroads as part of MxV Rail's Strategic Research Initiatives program, through the Federal Railway Administration (FRA), MxV Rail's internal research and development, and/or commercial customers.

  • Conduct data analysis, including, but not limited to: Exploratory Data Analysis (EDA).
  • Supervised machine learning model development and deployment.
  • Feature importance and interpretability analysis.
  • Statistical analysis of track, wheel, axle, and mechanical data.
  • Track and mechanical data collected at FAST or other sources.
  • Model development: Assist in building, training, and fine-tuning machine learning and deep learning models, with a primary focus on time series data (e.g., raw UT waveforms, electromagnetic data, other modalities).
  • Data processing: Participate in the collection, cleaning, and preprocessing of large datasets used for training and evaluating AI models.
  • Algorithm research: Conduct research on state-of-the-art algorithms and emerging AI technologies to improve the accuracy and efficiency of inspection systems.
  • Prototyping and testing: Develop proof-of-concept models and test them against real-world data to evaluate performance. Work with engineers to test and validate deployed models.
  • Code generation: Write clean, well-documented code in Python to support data pipelines, model building, and system integration.
  • Data Fusion: Explore data fusion approaches for UT and electromagnetic data.
  • Collaboration: Work closely with cross-functional teams to integrate AI/ML solutions into research.
  • Reporting: Document findings, methodologies, and results, and present progress to technical and non-technical stakeholders.
  • Ensures that all duties and responsibilities are performed in a safe manner.
  • Perform other related duties as assigned.
  • Open to learning and living the MxV Rail values (Momentum, Insight, Teamwork, Rigor, Purpose) in all facets of the organization's work.
  • Pursuing a Master's or PhD. in Industrial Engineering, Operations Research, Computer Science, Data Science, Electrical Engineering, or a related technical field.
  • Extensive experience in exploratory data analysis (EDA) and statistical analysis (coursework, research projects, or job experience).
  • Experience using Microsoft Office software.
  • Knowledge in AI/ML methods.
  • Knowledge of Python and/or R.
  • Willingness to learn about railroad operations, rolling stock, and maintenance concepts, literature review, multi-tasking, and strong communication & leadership skills.
  • Strong programming skills, with a preference for Python.
  • Completed coursework in machine learning, artificial intelligence, or computer vision.
  • Familiarity with at least one major machine learning framework, such as PyTorch or TensorFlow.
  • Fundamental understanding of machine learning concepts, algorithms, and evaluation metrics.
  • Strong analytical and problem-solving skills.
  • MxV Rail policy requires all prospective employees to complete a criminal background check (Disclosure for Consumer Reports Consent Form) and a pre-employment substance abuse screening (Applicant Consent for Drug Testing Form) as a condition of employment.
  • Extensive experience using Python or R.
  • Knowledge using SQL.
  • Strong foundations in AI /ML.
  • Knowledge of data manipulation and analysis libraries like NumPy and Pandas.
  • Experience with version control systems, such as Git.
  • Familiarity with cloud computing platforms (e.g., AWS, Azure, or GCP) for training models.
  • A portfolio of personal projects related to AI, ML, or computer vision is a plus.
  • Railroad Retirement
  • 401(k) Program with Company Match
  • Fortnight Schedule
  • Paid Holidays
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