Top Data Science Jobs in Edinburgh

As a Staff Data Scientist, you will lead model development, prepare datasets, and build foundational models for bioprocess data, enhancing speed and productivity for customers.

As a Data Scientist, you will develop data science solutions and machine learning models, collaborating with teams to solve business challenges.

As a Data Science Intern at QuantCo, you will tackle business challenges using statistical methods, analyze data, build machine learning models, and communicate insights.

The Senior Data Scientist will develop algorithms for generative AI, analyze data, train models, and innovate solutions tailored to the shipping and industrial sectors.

As a Data Science Manager, you'll lead Media Mix Modeling efforts, collaborate with cross-functional teams, analyze marketing effectiveness, and optimize budgets.

Data Scientists at QuantCo will create impact from data by analyzing and interpreting data, building machine learning models, and communicating results.

The Senior Data Scientist will develop R packages, consult on Biostats models, and collaborate on cloud solutions, driving high-impact outcomes for clients.

The Senior Data Scientist will apply machine learning to solve business problems, develop prototypes, and work with datasets across various Ringier divisions.

The Lead Data Scientist will utilize advanced analytical techniques to influence key business decisions, optimize marketing strategies, and support sales operations through data management and reporting.

As a Senior Full Stack Data Scientist, you will develop forecasting algorithms, collaborate with diverse teams, and drive innovation in inventory decision-making systems for the apparel industry.

As a Senior Full Stack Data Scientist, you will lead the development of forecasting algorithms, collaborate on innovative projects, and contribute to a greenfield machine-learning startup focused on inventory management.

The Sr Data Scientist will lead data science initiatives, design scalable solutions, and address data quality and model performance issues in a collaborative environment.