Data Scientist

Posted 8 Hours Ago
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London, England, GBR
Hybrid
Entry level
Artificial Intelligence • Software • Analytics • Automation
The Role
Analyze large datasets, apply statistical and machine learning models, perform data analytics, and create visualizations. Collaborate with founders and enterprise clients to solve complex business problems, embedding developed models into the Kepler AI platform. This early-stage role requires hands-on development, strong analytical communication, and comfort working in an ambiguous startup environment.
Summary Generated by Built In

Company Description

Ergodic AI is an AI startup based in London that is building an action-oriented AI platform to help enterprises move from analysis paralysis to rapid data-driven execution.

Kepler - our AI platform - identifies context, surfaces optimal actions and justifies the reasons for their execution. We're an early stage startup and are already working with multiple F500 enterprises.

We’re backed by leading VC funds to help further our mission and are now on the hunt for the brightest and best to join us.

Our Team

The founding team is highly experienced across a range of AI and commercial work, with careers in world class organisations and experience building and exiting $multi-million startups previously.

Process

As you progress through the process, you’ll meet each of the 3 founders who will probe you for your motivations, experiences and fit for the role.

Steps:

  • Application / CV screening

  • Interview with CTO

  • Interview with CSO

  • Interview with CEO

  • Decision

We aim to move quickly through the process and not waste your time.

The Role

This is a full-time hybrid role for a Data Scientist at Ergodic AI. As a Data Scientist, you will be responsible for analyzing large datasets, applying a range of  modelling techniques, performing data analytics, and creating data visualizations. 

You will work closely with the founders and our clients to identify and solve complex business problems using data-driven insights. Models that you build will be embedded into our platform - Kepler.

As an early stage hire, you will bring technical experience and hands-on development skills to shape our product as we unleash it on the world's most challenging data & AI problems.

You will receive meaningful equity and a competitive salary alongside all the tech you need to execute.

While the role is primarily located in the London Area, United Kingdom, there is flexibility for some remote work.

Qualifications

  • Data Science, Statistics, and Data Analytics skills

  • Data Visualization and Data Analysis skills

  • Strong proficiency in programming languages such as Python or R

  • Experience with machine learning and predictive modelling

  • Excellent problem-solving and analytical skills

  • Ability to communicate complex ideas and findings to both technical and non-technical stakeholders

  • Master's or Ph.D. degree in Data Science, Statistics, Computer Science, or a related field

  • Experience with LLMs - fine tuning and customising is a plus

  • Experience working with big data and cloud platforms is a plus

  • Comfort working in a startup environment (either through experience or desire) where ambiguity is the expectation but the potential to grow is huge

Skills Required

  • Data science, statistics, and data analytics skills
  • Data visualization and data analysis skills
  • Strong proficiency in Python or R
  • Experience with machine learning and predictive modeling
  • Excellent problem-solving and analytical skills
  • Ability to communicate complex ideas to technical and non-technical stakeholders
  • Master's or Ph.D. degree in Data Science, Statistics, Computer Science, or a related field
  • Experience with LLM fine-tuning and customization
  • Experience with big data and cloud platforms
  • Comfort working in a startup environment
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The Company
6 Employees
Year Founded: 2024

What We Do

Ergodic AI is a London-based AI startup developing enterprise world models and an action-oriented platform called Kepler. The platform models complex business operations, integrates data from multiple sources, and helps organizations predict disruptions, understand potential consequences, evaluate trade-offs, and choose effective actions before committing changes. Its applications include supply-chain optimization, forecasting, manufacturing, retail, healthcare, financial-services risk, and energy operations across complex enterprises.

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