Senior Python Data Science Engineer

Wild.Codes

London

1 month ago

Applications closed

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Our client is a mission-driven AI startup founded by a successful serial entrepreneur and AI policy advocate. The project focuses on building a next-generation forecasting platform powered by AI, aiming to outperform human experts in predicting elections, geopolitical events, and more.

The ultimate goal is to develop a powerful system that helps organizations and governments navigate uncertainty with data-driven predictions.

As aSenior Data Scientist / Backend Engineer, you will join at the ground floor of this venture, working directly with the founder to design and build the platform's core technology. This is a unique opportunity to take technical ownership of an early-stage product with real-world impact, work on cutting-edge AI applications, and help shape the future of the company.

What you will be working on:

Build the first version of a scalable, AI-powered forecasting system.
Design and develop backend infrastructure, data pipelines, and simple frontends for rapid prototyping.
Fine-tune large language models (LLMs) to improve forecasting accuracy.
Collaborate directly with the founder on architecture, design choices, and technical direction.
Contribute to the long-term vision and foundation for the platform, ensuring scalability and maintainability.

Requirements:

5-6+ years of professional experience in data science, backend engineering, or full-stack development.
Strong proficiency inPython, with experience usingpandas,NumPy, and relevant backend frameworks (Django or similar preferred).
Hands-on experience with AI/ML models; fine-tuning LLMs is astrong plus.
Solid understanding of software architecture, scalability, and system design.
Comfortable working in a fast-paced, early-stage startup environment.
Self-driven, able to make technical decisions, and contribute strategically.
Full professional English proficiency and excellent communication skills.

Bonus if you have:

Experience in forecasting, data modeling, or academic research.
Previous work in early-stage startups or building MVPs.
Strong opinions on technical architecture and a track record of implementing them.

If you’re excited about building meaningful AI products from scratch and being part of a high-impact project, we’d love to hear from you!

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