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Job Description

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Job Summary:

We are seeking a highly skilled Data Scientist to join our procurement technology team. The candidate will play a key role in designing and developing machine learning and LLM-driven solutions to automate and optimize sourcing and procurement operations. This role offers the opportunity to work on challenging problems, leverage state-of-the-art research, and build scalable models that enhance customer experience and business efficiency.


Key Responsibilities:

  • Analyze and extract relevant insights from large-scale datasets to drive automation and optimization.
  • Research, develop, and implement machine learning, LLM, and statistical models to improve user experience in procurement.
  • Build scalable ML solutions that address real-world business problems.
  • Collaborate with cross-functional teams to integrate models into production systems.
  • Stay updated with the latest research in AI/ML and apply innovative approaches to business challenges.


Basic Qualifications:

  • 5+ years of hands-on experience in building ML models for business applications.
  • Strong proficiency in

    Python

    and relevant ML/AI libraries.
  • Expertise in algorithms, data structures, and numerical optimization.
  • Solid experience with

    data mining, parsing, and handling large-scale datasets

    .
  • Experience in

    parallel, distributed, or high-performance computing

    .


Preferred Qualifications:

  • Experience working with

    Large Language Models (LLMs) and NLP

    applications.
  • Prior exposure to

    procurement, sourcing, or supply chain domains

    .
  • Understanding of deploying models at scale in production environments.
  • Familiarity with

    cloud-based ML environments (AWS, GCP, or Azure)

    .
  • Strong problem-solving ability with a mix of research-driven and pragmatic approaches.


Good to Have:

  • Hands-on experience with

    deep learning frameworks

    (TensorFlow, PyTorch).
  • Exposure to

    MLOps tools

    (MLflow, Kubeflow, SageMaker).
  • Research publications or contributions to the ML/AI community.

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