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GRIDSIGHT

Founding Customer Solutions Engineer

London
Posted 1 day ago
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About the role

Pilots here are moving from proposal to deployment with network operators. This role sits between electrical engineering thinking and real customer problems: turning analysis into insight a DNO or DSO can see, trust and act on, and working out how our product and data land in a market that is new for our models.

In our established customer teams, this work runs alongside Power Engineers on live accounts. Here it is a founding seat, forward deployed with the customer, with scope to decide how delivery in this region should work. You will be close to customers, close to the sales conversations that open them, and close to the product decisions that shape what we build next.

You will not inherit a playbook. You will write the one the next three hires use.

What you'll do

  • Turn network data (AMI, network topology and other asset telemetry) into clear analysis and visualisations that help a DNO or DSO understand the real state of its grid.
  • Stretch across the whole customer relationship: pre-sales, pilots, and full deployments.
  • Take the technical solution designed with Power Engineers and execute it end to end with the customer. You own the delivery, not only the analysis.
  • Wrangle messy, incomplete, real-world network data into something reliable, and be straight about data quality where it matters.
  • Sit close to customers in pilots and early deployments: run working sessions, present findings, and translate between technical and non-technical audiences.
  • Shape how our data model and platform fit UK and European network operators and their regulatory context, and feed the recurring patterns back to Product.
  • Build the delivery playbook for the region as you go, so the next hires move faster than you did.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

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Who you are

Must-haves

  • Strong analytical and data craft. You’ll have the data toolkit for real analysis, transformation and validation of messy datasets. Hands-on, not directing.
  • A bias for the most direct path to value. You work out what matters and why before working out how, and you do the simple thing first. You can point to ambiguous problems you turned into delivered outcomes, not only researched ones.
  • Commercial instincts. Comfortable in pre-sales conversations, prioritising by value to the customer and to us, and credible as much in front of a prospect as for a live customer.
  • Excellent customer-facing communication. You can explain complex analytics plainly, facilitate a room, and hold credibility with senior stakeholders.
  • Fast, demonstrable learning velocity in unfamiliar technical territory. Deep power systems expertise is not required. Building enough grid context quickly to find where the value is, and to design solutions rather than only execute them, is.
  • A demonstrated reason to be in energy. We don't need years in the sector. We do need to believe you would choose this problem.
  • AI-native working practices. You use AI and agentic tooling to move faster on analysis, prototyping, testing and documentation, and you hold a real method for checking correctness rather than trusting output.
  • Comfortable as an early hire. No established process, nobody above you doing the delivery, and no manager in the room to escalate to.
  • Strong analytical and data craft. You’ll have the data toolkit for real analysis, transformation and validation of messy datasets. Hands-on, not directing.

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Strongly preferred

  • Exposure to the energy sector, grid data, DER, digital twins, or energy-data infrastructure.
  • Experience owning outcomes with external customers or clients.

Nice-to-haves

  • ML or data science depth.
  • Experience with modern data tooling.
  • Familiarity with UK or European energy regulation and the DNO/DSO context.

How we work

We deliver work we take pride in, shipped at pace. Everyone owns outcomes end to end. We take on interesting, high stakes problems but they don't come with instructions or a playbook. We seek the fastest path to value for the customer and take it.

If you want real problems, real pace and the opportunity to do your life's work, we want to meet you.

What we offer

  • Competitive salary. We hold high expectations, but pay accordingly.
  • Meaningful ESOP so you share in the growth of Gridsight.
  • Work-from-home allowance, health and wellness allowance, bi-annual in-person working weeks.
  • A central London office and a flexible hybrid arrangement. We’re hiring founding team members in the region, so we do want you in the room with customers and with each other.
  • Trips to co-work with colleagues in Australia and the US.
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Skills

Data analysis
Data transformation
Data validation
Customer relationship management
Pre-sales
Technical communication
Stakeholder management
Grid data
Energy sector knowledge
AI-native working practices
Prototyping
Problem solving
Project delivery
Data visualization
Regulatory context
Analytical thinking

Location

London, England, United Kingdom

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