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Open nowPosted 21 days ago

Staff Data Analyst

tem20 open roles

Pay
£92,500 – £115,000 a year
Where
United Kingdom
Work mode
Remote
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Your applicationOpen nowStaff Data Analysttem · United Kingdom

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The clock on this job

Early applications get read.

13.7% of postings close within 7 days. Measured by our own scanner across the market. tem postings stay open a median of 22 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted 21 days ago

tem median: 22 days open

The posting

📈 Who We Are:

We are rebuilding the energy transaction, making it transparent and fair.

We're rebuilding how energy is bought and sold. That means cutting out middlemen, connecting businesses directly with renewable generators, and ensuring every transaction is traceable and transparent.

We're a 160+ person team - operators, data scientists, engineers, customer champions and energy experts - backed by top-tier investors including Lightspeed Venture Partners, Hitachi Ventures, Allianz, AlbionVC and Atomico. We closed a $75M Series B round in early 2026, taking our total funding to $94M, and we now power energy for over 4,000 UK businesses across 8,500+ sites, with over £75m in value returned to businesses and generators so far.

We're a technology company solving the energy industry, not an energy company. Some people call us a neo-utility, the neo-bank idea, applied to energy.

The industry is noticing. We were crowned Europe's Most Exciting Tech Company at the GP Bullhound Allstars awards https://www.gpbullhound.com/articles/allstars-awards-2026-winners-announced/, came in at #6 on LinkedIn's Top Startups 2026 https://www.linkedin.com/pulse/linkedin-top-startups-2026-20-uk-companies-rise-linkedin-news-uk-xoffc in the UK, #7 on the Scaling Europe 50 https://scalingeurope.co.uk/ of Europe's fastest-growing companies, and #14 on Sifted's AI 100 https://lnkd.in/p/ehxWgJyc.

Learn more about us on our website https://www.tem.energy/.

The Role

We're hiring a Staff Data Analyst.

This is not a reporting-only role. Embedded day to day within our commercial team, you'll be responsible for the core metrics that matter to the business - conversion rate, contracted volume, total sales, and margins - building on the pipeline tracking, forecasting and partner reporting that already exists. Priorities are set jointly with commercial; performance and development sit with the Analytics Manager, who you'll report into.

As a staff analyst, you'll take ambiguous commercial questions, decide the right approach, and turn analysis into clear recommendations rather than just presenting numbers. Success isn't measured by dashboards shipped - it's measured by whether stakeholders have metrics they understand and trust, analysis that changes what people do, and a team that can increasingly self-serve the answers it needs.

Responsibilities

Pipeline & Revenue Forecasting Accuracy

- Monitor the sales pipeline, catching and resolving cases where in-progress and confirmed revenue overlap or deals get double-counted.

- Define and report on forecast accuracy against annual targets, setting the standard for how commercial metrics are tracked across the team.

- Diagnose CRM data quality issues, such as parent-child asset relationships, that put pipeline and forecast reliability at risk.

Commercial Analysis & Insight

- Carry out commercial opportunity sizing and partner performance analysis to support sales and leadership decisions.

- Identify underperformance, emerging trends and risks in the pipeline before they surface in headline forecast numbers.

- Serve as the voice of data for the commercial team, translating complex analysis, including retention and renewal trends, into clear recommendations for senior stakeholders.

Partnership & Storytelling

- Work directly with commercial and sales stakeholders to understand what "good" looks like for their metrics, and translate that into clear, agreed definitions.

- Translate complex data into clear, compelling stories that inspire action among non-technical stakeholders.

- Increase data adoption across the commercial team so non-technical colleagues can self-serve for routine needs.

Requirements

Must haves

- Solid SQL skills, used to investigate complex datasets across modern analytics stacks (e.g. dbt, Omni or similar BI tools).

- Good commercial understanding, with an ability to connect analytical findings to revenue and margin outcomes.

- Experience developing forecasts or scenario models, and explaining the drivers behind variance from actuals.

- Ability to turn ambiguous stakeholder questions into well-defined analytical problems, and to present recommendations clearly to senior stakeholders.

- Proven experience building trusted metrics or reporting from messy or inconsistent source data (e.g. CRM, transactional systems).

Bonus points

- Experience in energy, fintech, or another commercially complex, data-heavy sector.

- Python for deeper statistical or data-quality work.

- Experience building metric frameworks that connect operational activity to commercial outcomes.

- Familiarity with CRM systems and parent-child/account hierarchy data structures.

Benefits & Perks

- Competitive salary 92,500-115,000GBP (or equivalent in your local currency)

- Stock options so everyone has ownership in our mission.

- 25 days holiday plus public holidays. Swap public holidays for the ones that matter most to you, and enjoy your birthday off.

- Remote first within the UK and Europe.

Interview Process

- Intro call with Talent, 30 minutes.

- Behavioural Interview with the Hiring Manager, 60 minutes.

- Technical Skills interview with the team, 75 minutes.

- Bar Raiser interview with leadership stakeholders, 45 minutes.

We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. If you’re excited about this role but not sure you meet every requirement, we’d still love to hear from you. Your unique perspective could be exactly what we’re looking for.

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