Fraud-Fighting ML Engineer: Cloud & MLOps Specialist

Fraud-Fighting ML Engineer: Cloud & MLOps Specialist

Full-Time 50000 - 65000 £ / year (est.) Home office (partial)
Smartnumbers

At a Glance

  • Tasks: Develop and maintain cloud-based ML platforms while engineering data pipelines.
  • Company: Join Smartnumbers, a forward-thinking tech company in London.
  • Benefits: Enjoy competitive salary, hybrid working, health insurance, and generous leave.
  • Other info: Be part of a dynamic team with exciting growth opportunities.
  • Why this job: Make a difference in fraud-fighting with cutting-edge machine learning technologies.
  • Qualifications: Experience in machine learning, Python, SQL, and AWS services required.

The predicted salary is between 50000 - 65000 £ per year.

Smartnumbers is looking for a Machine Learning Engineer to join their team in London. The role involves developing and maintaining cloud-based machine learning platforms, engineering data pipelines, and ensuring model performance using AWS and various ML technologies.

Candidates should have experience in machine learning, proficiency in Python and SQL, and a good understanding of AWS services.

Smartnumbers offers a competitive salary and benefits including hybrid working, health insurance, and generous leave.

Fraud-Fighting ML Engineer: Cloud & MLOps Specialist employer: Smartnumbers

Smartnumbers is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong focus on employee growth, we offer extensive training opportunities and a competitive benefits package, including hybrid working arrangements and health insurance, ensuring our team members thrive both personally and professionally.

Smartnumbers

Contact Details:

Smartnumbers Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Fraud-Fighting ML Engineer: Cloud & MLOps Specialist

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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 Smartnumbers.

Apply Directly through Our Website

When you find a suitable opening like Fraud-Fighting ML Engineer: Cloud & MLOps Specialist at Smartnumbers, 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 Fraud-Fighting ML Engineer: Cloud & MLOps Specialist

Python
Problem-Solving Skills
SQL
Data Engineering
Communication Skills
Data Pipeline Development
API Integration

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!

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Craft a Tailored Cover Letter:For a full-time role at Smartnumbers, 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 Smartnumbers. 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 Smartnumbers

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!

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Get Comfortable with Python and R

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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.