Senior Data Scientist

Quiet Capital; Greater London; On-site; GBP 75,000 - 120,000; Full time

Job summary

Quiet Capital is seeking a Research Data Scientist to turn messy, real-world industry data into AI-driven insights and products. You will explore data, design experiments, and prototype models that can be deployed with engineers to production-ready systems.

You will work on forecasting, optimization, and recommendation problems across sales, inventory, and operations, with a strong emphasis on rigorous experimentation and LLM applications in practical workflows.

Qualifications

• Master or PhD in math or science disciplines.
• 4+ years of hands-on data science/ML or a PhD plus 2+ years.
• Strong experimentation mindset with solid statistical reasoning.

Responsibilities

• Wrangle large, messy datasets from legacy systems into structured formats.
• Design, run, and evaluate experiments with rigorous statistics to validate hypotheses.
• Build and prototype ML models for forecasting, optimization, and recommendations.
• Explore and fine-tune LLMs for industry workflows.
• Collaborate with engineers to deploy research into production.
• Foster a culture of experimentation.

Skills

Python

pandas

NumPy

scikit-learn

XGBoost

PyTorch

Hugging Face

experiment design

evaluation metrics

Education

Master's/PhD in math/science

Tools

SQL

PostgreSQL

LLM fine-tuning

prompt engineering

Job description

We're hiring a Research Data Scientist to join us at an exciting early stage. You'll play a central role in helping us turn messy, real-world industry data into AI-driven insights and products. The role is a mix of data exploration, applied ML, and experimentation with LLMs. You'll be designing and running experiments, proving what works, and collaborating closely with engineers to turn research into production-ready systems.

What you will do:

• Wrangle large, messy datasets from legacy systems and real-world processes into structured, usable formats
• Design, run, and evaluate experiments with rigorous statistical methods to validate hypotheses and measure business impact
• Build and prototype ML models for forecasting, optimization, and recommendation across domains like sales, inventory, and operations
• Explore and fine-tune large language models (LLMs) for practical use cases in industry workflows
• Collaborate with engineers to take promising research into production
• Contribute to a culture of experimentation

What we look for:

• Scientific mindset (Master/PhD in math/science)
• Rigorous about experimentation and statistical reasoning
• 4+ years of hands-on experience in data science/ML/applied research or a PhD plus 2+ years
• Comfortable designing and running experiments with proper baselines, controls, and statistical evaluation
• Excited to explore and apply LLMs
• Thrive in a dynamic, iterative environment
• No industry knowledge required

Technical skillset - Must:

• Python
• common data science/ML libraries (e.g., pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face)
• experiment design
• evaluation metrics

Nice to have:

• LLM fine-tuning
• prompt engineering
• SQL/PostgreSQL