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Job details

Data Science Intern

Who We Are

Metal production accounts for 10% of all human generated greenhouse gases. One of the most effective paths to reducing those emissions is by maximizing our recovery of metals through recycling, which requires a fraction of the energy compared to mining.

VALIS’ mission is to lead a circular economy powered by data that protects the planet, its resources, and its inhabitants. We are a B2B SaaS company that provides next generation technology to metal recyclers enabling them to optimize their operations by making data-driven decisions. We’re focused on integrating and improving processes along the entire recycling chain, so the materials of yesterday are properly recovered to meet the demands of tomorrow. We’re an early-stage company, backed by leading climate-tech VC’s, looking to bring on new team members that can help us build VALIS and transform the industry. We lead with authenticity, boldness, passion, and empathy focused on creating a more sustainable future. A career at VALIS is one where you’ll be empowered to expand your technical and leadership abilities while having a positive impact on the world.

Role Overview

Summer Session:

40 Hours/Week

Approximate Start Date - June 1, 2025

Approximate End Date - August 31, 2025

This internship, supported by the MassCEC Clean Energy Internship program, will provide exposure to the metal recycling industry, real-world experience in tackling data science and computer vision problems, and the opportunity to lead project R&D execution. You'll work on a multidisciplinary team of materials and software engineers to apply your knowledge, build new technical and interpersonal skills, and gain exposure to a multitude of fields encompassed in a fast-moving SaaS startup solving problems in metals recycling and recovery. This position is well suited for computer/data science students looking to get practical project-based experience building data solutions for sustainability-centered innovation.

This role is primarily remote, but will require some in-person work at our Leominster, MA facility - you must be able to provide your own transportation. Additionally you must be able to work a consistent schedule each week until the end of the program - exact number of hours and schedule can be discussed further.

Key Responsibilities

  • Perform exploratory data analysis and statistical analysis using Python (pandas, NumPy, etc.)
  • Design and implement machine learning and analytical algorithms, particularly in the domain of computer vision (e.g., image classification, object detection, segmentation)
  • Implement proof-of-concept models and algorithms, build case studies for analytical solutions, and contribute to new feature development for the VALI-Sample product
  • Support the improvement of data management workflows, including data collection, cleaning, labeling, and storage
  • Collaborate with the software and product team to ideate and iterate upon building practical analytical solutions to solve problems in the metals recycling domain

Required Attributes & Skills

  • Live, or be a full time student at a University, in MA
    • Completed first year or 24 credits
    • Pursuing a degree in computer, data, or mathematical sciences, or a related field
  • Strong proficiency in Python and common data science libraries (e.g., pandas, scikit-learn, matplotlib)
  • Understanding of basic machine learning algorithms and model evaluation techniques
  • Ability to clearly communicate technical concepts

Advantageous Attributes & Skills

  • Experience working with image data or computer vision tasks (course work or project experience)
  • Background or knowledge in statistics and mathematics
  • Experience with SQL and database systems
  • Strong understanding of data structures and algorithms
  • Git version control experience
  • Paid internship position

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VALIS Insights specializes in software for optimized scrap metal sorting. Visit our website to learn more about our products and their solutions today.

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Internship, hybrid
DATE POSTED
May 3, 2025

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