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A leading financial services provider in Scotland is seeking an AI Ops Engineer to drive the design and implementation of data science tools. You'll work collaboratively with business stakeholders to identify suitable data solutions, maintain expertise in emerging trends, and lead projects using statistical and machine learning techniques. The ideal candidate will have substantial experience in data analysis, proficiency in AWS tools, and a quantitative degree. This role offers an exciting opportunity to leverage data for impactful customer solutions.
Join us as a AI Ops Engineer
We’re looking for someone to understand the requirements and needs of our business stakeholders. You’ll develop good relationships with them, form hypotheses, and identify suitable data and analytics solutions to meet their needs and to achieve our business strategy.
You’ll be maintaining and developing external curiosity around new and emerging trends within data science, keeping up to date with emerging trends and tooling and sharing updates within and outside of the team.
You’ll also be responsible for:
To be successful in this role, you’ll need evidence of project implementation and work experience gained in a data-analysis-related field as part of a multi-disciplinary team. We’ll also expect you to hold an undergraduate or a master’s degree in a quantitative discipline, or evidence of equivalent practical experience.
You’ll also need experience with statistical software, database languages, big data technologies, cloud environments and machine learning on large data sets. And we’ll look to you to bring the ability to demonstrate leadership, self-direction and a willingness to both teach others and learn new techniques.
Additionally, you’ll need:
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.