Coupa Software
Coupa Software
„Coupa Software“ kuria verslo išlaidų valdymo sprendimus, padedančius organizacijoms valdyti pirkimų, finansų, tiekimo grandinės ir IT išlaidas. Jos platforma palaiko sąskaitų faktūrų išrašymą ir tvarkymą, mokėjimus, išlaidų valdymą, santykių su tiekėjais valdymą ir bendradarbiavimą tiekimo grandinėje. Derindama dirbtinį intelektą su duomenų įžvalgomis, ji padeda nustatyti taupymo galimybes, gerinti atitiktį reikalavimams ir mažinti veiklos riziką. „Coupa“ aptarnauja įvairių sektorių organizacijas, įskaitant automobilių pramonės, sveikatos priežiūros, mažmeninės prekybos, logistikos ir konsultacijų įmones, o jos partnerių ir klientų bendruomenė siekia efektyvesnės ir atsparesnės verslo veiklos.

Senior Data Scientist, Sourcing AI, Prague Hybrid

Develop sourcing AI for Coupa’s spend management platform, taking models from real-world problem definition through production. Work across supplier discovery, forecasting, optimisation, and document understanding.

Aprašymas

  • Lead sourcing research from framing problems with real spend data through experimentation and production deployment
  • Create new sourcing approaches without depending on established baselines or ready-made solutions
  • Build datasets, labels, benchmarks, and supervision signals from historical events and outcomes
  • Plan and execute fast experiments, prototypes, baselines, and offline assessments
  • Extend Coupa’s internal T-LLM foundations for RFPs, specifications, quotes, and contracts
  • Account for inference cost, response time, resilience, and recommendation failure modes
  • Partner with Coupa’s Sourcing product, data, and AI Platform teams
  • Record technical decisions and help strengthen team practices
  • Investigate supplier recommendation and retrieval, forecasting and should-cost models, game theory and mechanism design, combinatorial optimisation, and multimodal document understanding

Reikalavimai

  • At least five years of experience in applied machine learning, data science, ML engineering, or quantitative research
  • A track record of deploying models or decision systems in production
  • Advanced Python proficiency
  • Experience working with SQL and large, untidy datasets
  • Expertise in at least one of these areas: deep learning, recommendation and ranking, forecasting and time series, optimisation 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 discipline
  • A rigorous approach to data leakage, baselines, and evaluation that reflects production conditions
  • Ability to work effectively in greenfield and ambiguous problem spaces
  • Interest in procurement, supply chains, or market design is useful but optional

Privalumai

  • Access to frontier LLMs, high-end GPUs, and large-memory training clusters
  • Funding for relevant conference attendance
  • 33 days of leave covering PTO, personal days, a birthday day, and two company wellness days
  • Parental leave
  • Two paid company-wide wellness days each year
  • A paid day off for your birthday
  • 40 hours of paid volunteer leave each year
  • Confidential Employee Assistance Program available 24/7/365 at no cost
  • Zurich Travel Assist protection for business travel
  • Cash referral bonuses
  • Comprehensive medical and dental insurance based on location
  • Retirement or pension plans based on location
  • Life or accident coverage based on location
  • Prague Karlín workspace with an inspiring setting and complete technology setup
  • 200 m² terrace overlooking Prague Castle

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