At a Glance
- Tasks: Drive data science tools and implement advanced analytics solutions for customer success.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on emerging trends in data science.
- Why this job: Make a real impact by using your data science skills to solve complex business problems.
- Qualifications: Degree in a quantitative field or equivalent experience; strong data analysis and leadership skills.
The predicted salary is between 36000 - 60000 € per year.
Join us as an AI Ops Engineer. In this role, you’ll drive and embed the design and implementation of data science tools and methods, which harness our data to drive market-leading customer solutions. Day-to-day, you’ll act as a subject matter expert and articulate advanced data and analytics opportunities, bringing them to life through data visualisation.
If you’re ready for a new challenge, and are interested in identifying opportunities to support external customers by using your data science expertise, this could be the role for you.
What you’ll do:
- Understand the requirements and needs of our business stakeholders.
- Develop good relationships with them, form hypotheses, and identify suitable data and analytics solutions to meet their needs and achieve our business strategy.
- Maintain and develop 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.
- Proactively bring together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques, and algorithms.
- Implement ethically sound models end-to-end and apply software engineering and a product development lens to complex business problems.
- Work with and lead both direct reports and wider teams in an Agile way within multi-disciplinary data to achieve agreed project and Scrum outcomes.
- Use your data translation skills to work closely with business stakeholders to define business questions, problems or opportunities that can be supported through advanced analytics.
- Select, build, train, and test complex machine models, considering model valuation, model risk, governance, and ethics throughout to implement and scale models.
The skills you’ll need:
- Evidence of project implementation and work experience gained in a data-analysis-related field as part of a multi-disciplinary team.
- An undergraduate or master’s degree in a quantitative discipline, or evidence of equivalent practical experience.
- Experience with statistical software, database languages, big data technologies, cloud environments and machine learning on large data sets.
- Demonstrated leadership, self-direction and a willingness to both teach others and learn new techniques.
- Proficient in key AWS tools including EMR, Airflow, DynamoDB, S3, RDS, ElasticBeanStalk, EC2, Kinesis, Lambda and CloudWatch.
- Experience using Java, Scala, Spark, Python, shell, pyspark along with experience in DevOps Tools like Git, Bitbucket, Jenkins and Artifactory.
- Strong ability to debug complex data issues from Splunk, Spark and CloudWatch audit logs, working closely with stakeholders to manage customer incidents and support service management.
- Experience in model deployment, fine-tuning, inference optimization.
- Experience in model versioning, drift detection, pipelines such as MLflow and Kubeflow.
AI Ops Engineer in Edinburgh employer: NatWest Group
As an AI Ops Engineer with us, you'll be part of a dynamic and innovative team that values collaboration and continuous learning. Our work culture fosters creativity and encourages you to stay ahead of emerging trends in data science, while our commitment to employee growth ensures you have access to training and development opportunities. Located in a vibrant area, we offer a supportive environment where your expertise can thrive, making a meaningful impact on our customers and the industry.
StudySmarter Expert Advice🤫
We think this is how you could land AI Ops Engineer in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, visualisations, and any machine learning models you've built. This will give you an edge and demonstrate your expertise to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in AI and data science. Be ready to discuss how you've tackled complex problems and how you can bring value to the team.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace AI Ops Engineer in Edinburgh
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Ops Engineer role. Highlight your experience with data science tools and methods, and don’t forget to mention any relevant projects you've worked on that align with our needs.
Showcase Your Skills:We want to see your technical skills shine! Be specific about your experience with AWS tools, programming languages, and machine learning techniques. Use examples to demonstrate how you've applied these skills in real-world scenarios.
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your passion for data science and how you can contribute to our mission. Make it personal and engaging!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at NatWest Group
✨Know Your Data Science Tools
Make sure you’re well-versed in the key AWS tools mentioned in the job description, like EMR and Lambda. Brush up on your knowledge of machine learning frameworks and be ready to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your ability to tackle complex data issues. Think about specific instances where you debugged problems or implemented solutions, and be ready to explain your thought process during the interview.
✨Understand Stakeholder Needs
Demonstrate your ability to communicate effectively with business stakeholders. Prepare to discuss how you’ve previously identified their needs and translated them into actionable data solutions. This will show that you can bridge the gap between technical and non-technical teams.
✨Stay Updated on Trends
Keep yourself informed about the latest trends in data science and analytics. Be prepared to share insights on emerging technologies or methodologies that could benefit the company. This shows your passion for the field and your commitment to continuous learning.
