At a Glance
- Tasks: Build and deploy machine learning models for personalisation and data insights.
- Company: Join a forward-thinking tech company with a collaborative vibe.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Exciting career growth potential in a modern ML Ops setting.
- Why this job: Make an impact with cutting-edge technology in a dynamic environment.
- Qualifications: 3+ years in machine learning, proficient in Python and SQL.
The predicted salary is between 63000 - 77000 £ per year.
This is an exciting opportunity for someone who is passionate about technology, data, and machine learning, and is eager to contribute to a forward-thinking, collaborative environment. The Data Scientist will be responsible for building and deploying machine learning models to support personalisation, recommendations, anomaly detection, and data insights. The role involves working within modern ML Ops practices and leveraging AI-powered development tools to increase efficiency and scale.
Key Responsibilities
- Develop and deploy machine learning models for various use cases including personalisation and anomaly detection
- Implement ML Ops practices including monitoring, continuous integration, and automated retraining
- Use AI-assisted development tools such as Cursor and Copilot to enhance productivity
- Collaborate with engineers, DevOps, and leadership to ensure robust data pipelines and translate business requirements into technical solutions
Requirements
- 3+ years of hands-on experience in applied machine learning and deploying production models
- Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience with AWS services and Databricks; understanding of ML Ops is highly beneficial
- Ability to quickly adapt to new tools and independently deliver scalable solutions
- Familiarity with data pipelines involving Kafka, Debezium, S3, Lambda, and Delta Lake is a plus
Apply now to find out more!
Data Scientist employer: Ronald James
As an Information Security Manager at our fast-growing B2B technology business, you'll thrive in a dynamic work culture that prioritises innovation and collaboration. We offer competitive benefits, including professional development opportunities and a commitment to employee growth, ensuring you can advance your career while making a meaningful impact on our governance and compliance strategies. Join us in a location that fosters creativity and teamwork, where your expertise will be valued and your contributions will drive our success.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨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 Ronald James!
✨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 Data Scientist at Ronald James.
✨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 Ronald James.
✨Apply Directly through Our Website
When you find a suitable opening like Data Scientist at Ronald James, 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 Data Scientist
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 Ronald James, 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 Ronald James. 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 Ronald James
✨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 Ronald James!
✨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.
