Lead Data Scientist

Omnis Partners
London
1 month ago
Applications closed

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🚀 JOIN THE FASTEST GROWING START-UP IN TOWN 🚀

Lead Data Scientist – Commercial


âś…Innovative, collaborative culture, business driven by AI

âś…Inspiring leader, passionate about this disruptive proposition with strong green impact

âś…Chance to own shares in scaling organisation, drive towards exit and IPO


đź“ŤLondon Hybrid

💸£125k

đź’ŽEquity



This is a senior, hands-on data science role for someone who thrives in fast-moving environments and wants their work to directly shape commercial decisions at scale.



You’ll sit within a high-performing finance function, owning advanced forecasting, modelling, and decision frameworks that influence revenue, cost, and strategic planning. This is not a reporting or dashboarding role — models built here are actively used to guide decisions under real time pressure, with real financial consequences.



The environment is high-velocity and demanding. Priorities move quickly, assumptions are challenged daily, and clarity of thinking under pressure is essential. You’ll be expected to operate with autonomy, bring structure to ambiguity, and deliver robust, explainable outputs that senior stakeholders trust.



Technically, this role suits a data scientist with strong Python and SQL, deep experience in forecasting and predictive modelling, and the ability to translate complex analysis into clear commercial insight. You’ll work closely with finance leaders and engineers alike, bridging modelling, systems, and decision-making.



This opportunity is best suited to someone who enjoys accountability, pace, and building things that matter — and who is energised by intensity rather than overwhelmed by it.



Experience Required:

  • Educated to degree level in a relevant subject such as Computer Science, Machine Learning, Artificial Intelligence, Mathematics, Statistics, Physics, Chemistry, Engineering etc.
  • Strong programming skills with Python, building algorithms and models, and working with large, messy, complex data sets to model optimised process and performance.
  • A deep background in applied data science within a commercial context, comfortable with fast paced, rapid growth culture.
  • Experience of working in a client or business-facing environment, demonstrable skills in building trust and commercial discourse around leveraging ML and AI to solve real-world business problems.
  • A proactive mindset, intellectual curiosity, and the ability to thrive in a fast-changing environment.

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