Coupa Software
Coupa Software
Coupa Software develops business spend management solutions that help organizations manage procurement, finance, supply chain, and IT spending. Its platform supports invoicing, payments, expense management, supplier relationship management, and supply chain collaboration, combining AI with data insights to identify savings, improve compliance, and reduce operational risk. Coupa serves organizations across sectors including automotive, healthcare, retail, logistics, and consulting, with a partner and customer community built around more efficient, resilient business operations.

Lead Data Scientist - Sourcing (Prague Hybrid)

Lead applied machine learning research for sourcing decisions using Coupa’s in-house T-LLM architectures and modern ML. Build and deploy production models for Coupa’s global spend management platform.

Description

  • Lead sourcing research initiatives from problem definition and experimentation through production deployment
  • Create novel solutions for new sourcing challenges
  • Define datasets, labels, benchmarks, and evaluation methods using historical sourcing events
  • Design and conduct experiments, prototypes, baselines, and offline evaluations
  • Apply in-house T-LLM architectures to RFPs, specifications, quotes, and contracts
  • Deploy models optimized for inference cost, latency, robustness, and recommendation accuracy
  • Partner with Coupa’s Sourcing, data, and AI Platform teams
  • Document technical decisions and support team development
  • Build systems for recommendation, retrieval, forecasting, should-cost analysis, game theory, mechanism design, optimization, and multimodal document understanding

Requirements

  • At least 10 years of experience in applied machine learning, data science, ML engineering, or quantitative research
  • Experience putting machine learning models or decision systems into production
  • Advanced Python skills
  • Experience working with large-scale, messy datasets
  • Proficiency with SQL
  • Ability to create reliable datasets, labels, and benchmarks
  • Expertise in at least one of deep learning, recommendation and ranking, forecasting and time series, optimization and operations research, causal inference and econometrics, reinforcement learning and bandits, market and mechanism design, or LLM-based systems
  • Strong experimental design skills and scientific rigor
  • Understanding of data leakage, baselines, and production-ready evaluation
  • Comfort solving ambiguous problems in greenfield environments
  • Interest in procurement, supply chains, or market design is welcome but not required

Benefits

  • Access to frontier LLMs, high-end GPUs, and large-memory computing clusters
  • Conference attendance budget
  • 33 days of leave, including PTO, personal days, birthday leave, and two company wellness days
  • Parental leave
  • Paid global wellness days
  • Paid birthday leave
  • 40 hours of paid volunteer leave each year
  • Free, confidential Employee Assistance Program available 24/7/365
  • Business travel protection through Zurich Travel Assist
  • Employee referral bonus program
  • Location-specific medical and dental insurance
  • Retirement or pension plans
  • Life or accident insurance protection
  • Prague workspace with full technical setup and a 200 m² terrace

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