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Salary
≈ $53k – $109k per year (Estimated)
Location
In office (London)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 8, 2026. Applied Computing scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Applied Computing delivers industrial AI to the energy industry including oil and gas, refineries, and petrochemical plants, helping critical operations harness 100% of their data and optimise in real time for safer, faster, higher-performing decisions.
Backed by Conception X

About Applied Computing

Applied Computing was founded in 2024 to build Orbital, a physics-informed foundation model for energy operations. We’re live across oil and gas, refineries, and petrochemicals, working towards our mission: sustainable abundance for a growing planet.

The hydrocarbon industry keeps the world running. But its complexity has left operators tied to legacy systems, making critical decisions on less than 10% of available data.

We built Orbital to change that. It’s a foundation model built specifically for energy that lets companies use AI at scale, harnessing all of their operational data and optimising in real time for any metric. Decisions get faster, operations get safer, and carbon intensity falls.

We’ve raised over $32 million, including one of the largest seed rounds for an AI company in the UK. We’re just getting started.

The Role

As a Business Analyst on our Project Management team, you’ll help ensure that our delivery of Orbital to customers across oil & gas, refining, and petrochemicals is well-organised, data-driven, and continuously improving. You’ll work closely with Project Managers, Engineering, and Customer teams to track delivery performance, surface insights from project and operational data, and help us make faster, better-informed decisions as we scale.

This is a great opportunity for a recent graduate with a strong quantitative background ( ideally in Data Science, Computer Science, or a related field) who wants to apply analytical thinking to real-world, high-impact problems in the energy industry, at an early-stage startup where you’ll have genuine ownership from day one.

What You’ll Do

  • Support Project Managers in tracking timelines, budgets, resourcing, and deliverables across multiple concurrent customer deployments

  • Build and maintain dashboards and reports that give leadership and delivery teams clear visibility into project health and performance

  • Analyse project and operational data to identify trends, risks, and opportunities for process improvement

  • Gather and document requirements from internal and customer stakeholders to support project scoping and planning

  • Partner with Engineering, Data Science, and Customer Success to translate business needs into clear, actionable project plans

  • Help develop and refine internal processes, templates, and tools as the Project Management function scales

  • Prepare data-driven summaries and materials for internal reviews and customer-facing updates

  • Spot opportunities to apply automation or lightweight tooling to streamline recurring analysis and reporting work

About You

  • A degree in Process Engineering, Data Science, Computer Science, or another quantitative field (or equivalent practical experience)

  • Strong analytical skills and confidence working with data. Spreadsheets and SQL as standard, with scripting experience (e.g. Python) a plus

  • Excellent written and verbal communication, with the ability to turn data into clear insights for both technical and non-technical audiences

  • Highly organised, with strong attention to detail and comfort managing multiple priorities at once

  • A proactive, curious mindset. Comfortable asking questions, challenging assumptions, and figuring things out in a fast-moving startup environment

  • Genuine interest in energy, industrial operations, or applying AI to real-world problems

  • No prior professional experience required, we’re looking for strong fundamentals and a hunger to learn and contribute

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