Senior Data & ML Ops Engineer (Hybrid)

Senior Data & ML Ops Engineer (Hybrid)

Full-Time 60750 - 74250 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Build and operate scalable fintech solutions with a focus on cloud-native architecture.
  • Company: Join Starling, the UK's leading digital bank known for fast technology and fair service.
  • Benefits: Enjoy a hybrid work arrangement, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic work environment with excellent career advancement opportunities.
  • Why this job: Make a real impact in fintech by collaborating with cross-functional teams on innovative projects.
  • Qualifications: Experience in data engineering and ML Ops, with a passion for customer-centered design.

The predicted salary is between 60750 - 74250 £ per year.

Starling is the UK’s leading digital bank, delivering fast technology and fair service for customers.

We seek a talented Full Stack Engineer (ML Ops) to build and operate scalable fintech solutions with a strong focus on cloud-native architecture and end-to-end ownership.

Hybrid work arrangement with offices across the UK; you’ll collaborate in cross-functional teams to ship robust features, driven by data and customer-centered design.

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Senior Data & ML Ops Engineer (Hybrid) employer: Muzz

Muzz is an exceptional employer that fosters a vibrant and collaborative work culture, perfect for creative minds looking to make a significant impact. With a focus on employee growth, you will have the opportunity to lead innovative projects while working alongside talented individuals in a hybrid environment in London. Join us to be part of a forward-thinking team dedicated to building a billion-dollar app that resonates with diverse communities across Europe.

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Contact Details:

Muzz Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data & ML Ops Engineer (Hybrid)

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Muzz!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data & ML Ops Engineer (Hybrid) at Muzz.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Muzz.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Data & ML Ops Engineer (Hybrid) at Muzz, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data & ML Ops Engineer (Hybrid)

Full Stack Development
ML Ops
Cloud-Native Architecture
Scalable Solutions
Cross-Functional Collaboration
Data-Driven Design
Customer-Centered Design

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 Muzz, 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 Muzz. 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 Muzz

✨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 Muzz!

✨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.