A very well-funded AI start-up, with presence across Europe, US and the Middle East, is looking for a Principal Data Scientist/MLE, who's an expert in Time Series.

Having just raised one of the largest Series A funding rounds in the sector, they are looking to make a number of strategic senior hires to help take the business to the next level.

This pivotal role merges cloud infrastructure, DevOps practices, and advanced machine learning to automate and deploy sophisticated computational models tailored for time series data across diverse industries. You'll lead the development of innovative solutions, driving the company's technological evolution with a focus on forecasting, predictive analytics and dynamic data modelling.

Salary:ideally up to ~£140k (but there's flexibility for exceptional candidates)

+ generous equity

Location:Old Street (3-4 office days/week)

✅ Must have requirements:

• Experience designing and deploying machine learning models that excel in forecasting, anomaly detection, and pattern recognition within time series data
• Experience building robust pipelines specifically designed for time series data workflows, ensuring scalability, efficiency, and seamless flow from data ingestion to model deployment
• Experience developing scalable algorithms that are accurate and adaptable for time series data, ensuring reliable predictions and insights from evolving datasets
• Expertise in Python and SQL
• Significant experience using time series libraries (e.g. Statsmodels, Facebook Prophet, TensorFlow Time Series)
• Strong cloud expertise - ideally AWS
• Proficiency with CI/CD tooling (e.g. Github Actions, Jenkins, AWS CodePipeline)
• Great written and verbal communication skills

Bonus points for:

• Experience leading projects focused on time series forecasting and analysis, demonstrating the ability to mentor teams and manage cross-functional projects
• Advanced knowledge in applying deep learning techniques (using TensorFlow, PyTorch) to time series data, enhancing predictive accuracy and model complexity
• Having worked in a rapidly growing, product-focused start-up
• Strong academic pedigree (MSc or PhD) in a related field
• A strong understanding of AI ethics and privacy considerations, especially in the context of time series data
• Exposure to geospatial data sets
• Understanding of consumer behaviour and operational decision data
• Experience in optimisation and simulation