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Sr. Data Scientist

Job in Chicago, Cook County, Illinois, 60290, USA
Listing for: Zoro Tools, Inc.
Full Time position
Listed on 2026-10-18
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software), Data Analyst
Salary/Wage Range or Industry Benchmark: 105100 - 175100 USD Yearly USD 105100.00 175100.00 YEAR
Job Description & How to Apply Below

is a leading eCommerce platform offering nearly 12 million tools, parts and supplies for our business customers. Launched in 2011, we brought a B2C-like experience to the B2B industry, and continue to be at the forefront of digital innovation at the intersection of technology and distribution. We have rapidly grown to over $1 billion in annual revenue and we’re just getting started!

Position

Description:

As a Data Sr. Scientist I at Zoro, you’ll apply your expertise in machine learning, deep learning, statistical modeling, and data analysis to solve a variety of business challenges. From forecasting and customer segmentation to improving onsite search and recommendations, our team directly enhances our customers' experiences and informs critical business decisions. At Zoro, every day brings new challenges and opportunities to innovate.

Duties and Responsibilities:

  • Apply domain and industry knowledge to solve complex data science projects, developing advanced machine learning models, and driving data-driven decisions within the organization.
  • Lead data science projects from start to finish by refining objectives, developing a project plan and methodology, and collaborating with business and technical teams.
  • Write and maintain high-quality, production grade code, including unit and integration tests.
  • Establish and maintain comprehensive, accurate evaluation frameworks to assess model performance and inform ongoing improvements.
  • Collaborate with other data scientists to develop and implement algorithms, write code, evaluate relevant academic research to deliver final outputs.
  • Provide guidance on tools, practices to drive efficiency, technical debt, data sources, and best practices.
  • Mentor and guide junior data scientists on algorithms, coding best practices, and other technical concepts.
  • Document code and data science processes that are critical to the company and develop strategies to ensure those processes are robust and fault-tolerant.
  • Communicate findings to business leaders and colleagues using data visualizations, presentations and reports.

Minimum Qualifications:

  • Master’s degree in quantitative fields such as Statistics, Data Science, Computer Science, and other STEM disciplines.
  • 6+ years of experience leading data science projects that have a direct impact on a company’s objectives or PhD degree in quantitative fields such as Statistics, Data Science, Computer Science with 4+ years of experience.
  • 6+ years of experience applying data mining and machine learning to solve complex business problems, including 5+ years of hands‑on experience using deep learning frameworks to develop, train, and optimize machine learning models.
  • Deep understanding of relevance, ranking, and building representation‑learning solutions, with 2+ years of hands‑on experience developing and optimizing learning‑to‑rank models, utilizing and tuning for ranking and relevance metrics.
  • 5+ years of experience leveraging Python to process large, complex, and diverse datasets, develop and product ionize predictive models, and deploy scalable machine learning solutions across cloud-based and distributed computing environments.
  • 5+ years of experience with advanced SQL and cloud-based data platforms, such as Google Cloud Platform or AWS.
  • 3+ years of experience applying large language models (LLMs), generative AI in business use cases, including experience designing evaluation frameworks to assess model quality, relevance, and business impact through offline metrics.
  • Strong knowledge of statistical, causal inference methods, parametric models, and planning experiments.
  • Hands‑on application of SOLID principles and modern software engineering practices, including designing maintainable, testable, and scalable production systems.
  • Strong…
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