At a Glance
- Tasks: Transform data science prototypes into scalable, production-ready solutions and optimise machine learning pipelines.
- Company: Join a dynamic government team focused on innovative data engineering and AI solutions.
- Benefits: Enjoy 25 days annual leave, flexible working options, and a generous pension contribution.
- Other info: Be part of a supportive environment that values work-life balance and career growth.
- Why this job: Make a real impact by solving complex data challenges and collaborating with talented data scientists.
- Qualifications: Experience in data engineering and machine learning, with strong collaboration skills.
The predicted salary is between 44241 - 44241 £ per year.
Can you work with technical and non-technical stakeholders to deliver data-driven outcomes? Do you enjoy solving complex data engineering and machine learning challenges? Have you built and optimised data pipelines that support analytical and AI use cases? If so, we’d love to hear from you!
A Senior Data Engineer (ML) works within a rapid prototyping team alongside data scientists to develop, test, and scale data science solutions. They are responsible for ensuring that prototypes are production-ready, scalable, and maintainable. The role bridges data science and data engineering, enabling the team to deliver high-impact, operational AI solutions.
Joining our department comes with many benefits, including:
- Employer pension contribution of 28.97% of your salary.
- 25 days annual leave, increasing by 1 day each year of service (up to a maximum of 30 days annual leave), plus 8 bank holidays and a privilege day for the King’s birthday.
- Flexible working options where we encourage a great work-life balance.
As our Senior Data Engineer (ML), you’ll transform data science prototypes into secure, scalable, production-ready solutions. Working alongside data scientists, you’ll lead MLOps, CI/CD and model development and drift practices, optimise machine learning pipelines, champion responsible AI, and establish engineering standards that will support the Agency’s growing data and AI capability.
Your responsibilities will include, but aren’t limited to:
- Work within the data science team to deliver rapid prototypes for new solutions, developing new solutions using cutting-edge techniques.
- Collaborate with and translate data science prototypes into scalable, production-grade machine learning systems using robust engineering practices and automation pipelines.
- Design and implement scalable machine learning pipelines using modern MLOps tools and frameworks.
- Utilising Prototype-to-Production engineering.
- Apply internal data engineering best practices to ensure data quality, lineage, and reproducibility.
- Maintain continuous integration and deployment workflows for machine learning models, including automated testing, validation, and monitoring.
- Use tools such as MLflow, Databricks, and infrastructure-as-code to ensure reproducibility and reliability.
- Monitor deployed models for performance degradation, drift, and fairness.
- Implement retraining strategies and version control to maintain model integrity over time.
For further information on the role, please read the role profile. Please note that the role profile is for information purposes only - whilst all elements are relevant to the role, they may not all be assessed during the recruitment process.
Senior Data Engineer (Machine Learning (ML) in Southampton employer: Allscreens Nationwide Ltd
Allscreens Nationwide is an exceptional employer, offering a supportive team culture where employees are valued and encouraged to thrive. With access to state-of-the-art training facilities and opportunities for career progression, our Automotive Glazing Technicians in Birmingham can expect not only competitive bonuses but also the chance to work with the latest technology in the industry. Join us and be part of a company that prioritises both employee well-being and customer satisfaction.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Machine Learning (ML) in Southampton
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Senior Data Engineer (Machine Learning (ML) in Southampton
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Allscreens Nationwide Ltd, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Allscreens Nationwide Ltd. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Allscreens Nationwide Ltd
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Allscreens Nationwide Ltd!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
