Applied AI Scientist - Real-World Forecasting

UiPath

London

Hybrid

NOK 1,119,000 - 1,772,000

Full time

12 days ago
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Job summary

UiPath is seeking a Forward Deployed Scientist II to work with leading retailers and manufacturers on high-stakes AI problems in supply chain, forecasting, and pricing. You will own the science end-to-end, from understanding messy real-world data to shipping solutions that drive commercial impact.

You will apply cutting-edge ML and agentic AI techniques, translating field learnings into product direction while collaborating across data scientists and customer executives.

Qualifications

  • Strong track record applying ML / data science to real-world commercial problems, ideally with depth in forecasting, optimisation, or supply-chain / pricing.
  • Fluent programming (Python and SQL) and the ability to pick up whatever a problem demands.
  • Excellent communication — you can explain a complex model to non-technical stakeholders.

Responsibilities

  • Own customer engagements end-to-end — frame the problem, build the solution, and drive it to real commercial impact with customer teams.
  • Apply frontier ML, forecasting, and optimisation techniques — including agentic AI — to hard problems.
  • Turn field insights into product direction to improve core capabilities for future customers.
  • Operate with autonomy across stakeholders, and ship impactful solutions.
  • Stay at the edge of applied AI and bring insights back to the team.

Skills

ML / Data science
Forecasting
Optimization
Supply chain / pricing
Python
SQL
Excellent communication

Job description

UiPath is seeking a Forward Deployed Scientist II to work with leading retailers and manufacturers on high-stakes AI problems in supply chain, forecasting, and pricing. You will own the science end-to-end, from understanding messy real-world data to shipping solutions that drive commercial impact.

You will apply cutting-edge ML and agentic AI techniques, translating field learnings into product direction while collaborating across data scientists and customer executives.

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