who can delight our customers by continually learning and inventing. Our ideal candidate is an experienced Applied Scientist who has a track record of statistical analysis and building models to solve real business problems, with strong communication skills, and a passion for fairness and explainability in ML systems. The More ❯
marketing and trading. You have strong quantitative skills, including familiarity with Excel/VBA, R, and/or Python and their respective data manipulation, statisticalmodelling, and visualization packages. What's in it for you: You'll be doing work in the forefront of the commodity trading industry More ❯
on a corporate-wide set of client, investor, and operational problems. Build and maintain tools and services supporting the full model development lifecycle for statistical models, machine learning, optimization, and deep learning models (e.g., feature engineering, backtesting and simulation, validation, deployment). Maintain and monitor production models and experimentation. More ❯
The team, primarily based in Edinburgh, Scotland, is rapidly expanding. Our ideal candidate is an experienced Applied Scientist who has a track record of statistical analysis and building models to solve real business problems, has great leadership and communication skills, and has a passion for fairness and explainability in More ❯
other data science techniques, with dedicated access to our new GPU server with state-of-the-art compute. Projects will typically involve implementation of statistical models, data analysis pipelines, or deep learning architectures for various tasks, including computer vision, time-series analysis, high-dimensional clustering or large language models. … science, artificial intelligence, statistics, biomedical/biological sciences). Experience in a role involving data science, including managing, structuring, visualizing, analyzing data, and building statistical or machine learning tools. Fluency in one or more data science programming languages (R, Python with NumPy/pandas etc, Julia) with experience in More ❯
other data science techniques, with dedicated access to our new GPU server with state-of-the-art compute. Projects will typically involve implementation of statistical models, data analysis pipelines, or deep learning architectures for various tasks, including computer vision, time-series analysis, high-dimensional clustering, or large language models. … science, artificial intelligence, statistics, biomedical/biological sciences). Experience in a role involving data science, including managing, structuring, visualizing, analyzing data, and building statistical or machine learning tools. Fluency in one or more data science programming languages (R, Python with NumPy/pandas etc, Julia) with experience in More ❯
knowledge of deploy and release services, automation, and troubleshooting Experience of utilising tools and technology across the software development lifecycle Experience using mathematical and statistical models to assess trends Strong communication skills with the ability to proactively engage with a wide range of stakeholders In depth experience with observability More ❯
City, Edinburgh, United Kingdom Hybrid / WFH Options
ENGINEERINGUK
has grown to 30+ data scientists and data engineers. Working collaboratively, the team is multi-disciplinary with the following skills and capabilities: machine learning, statistical modeling, signal detection, natural language processing, data visualization, network/graph modeling, ETL, data pipelines, data architecture, communication, product management and strategy. We work … on a corporate-wide set of client, investor, and operational problems. Build and maintain tools and services supporting the full model development lifecycle for statistical models, machine learning, optimization, and deep learning models (e.g., feature engineering, backtesting and simulation, validation, deployment). Maintain and monitor production models and experimentation. More ❯
has grown to 30+ data scientists and data engineers. Working collaboratively, the team is multi-disciplinary with the following skills and capabilities: machine learning, statistical modeling, signal detection, natural language processing, data visualization, network/graph modeling, ETL, data pipelines, data architecture, communication, product management and strategy. We work … on a corporate-wide set of client, investor, and operational problems. Build and maintain tools and services supporting the full model development lifecycle for statistical models, machine learning, optimization, and deep learning models (e.g., feature engineering, backtesting and simulation, validation, deployment). Maintain and monitor production models and experimentation. More ❯
