At a Glance
- Tasks: Develop and deploy machine learning solutions while collaborating with cross-functional teams.
- Company: Dynamic company in London focused on innovation and inclusivity.
- Benefits: Competitive salary, hybrid work model, and a culture that values diversity and growth.
- Other info: Join a supportive team that encourages knowledge sharing and personal development.
- Why this job: Make a real impact with your data skills in a fast-paced environment.
- Qualifications: Experience in machine learning, proficient in Python and SQL, strong problem-solving skills.
The predicted salary is between 50000 - 70000 £ per year.
Location: Hybrid, London.
Responsibilities
- Contribute to the development of machine learning solutions from design through to deployment.
- Build and evaluate predictive models using Python and SQL.
- Translate business challenges into structured data science problems.
- Conduct statistical analysis and feature engineering to generate actionable insights.
- Support A/B test design, evaluation, and interpretation with rigour and clarity.
- Collaborate with stakeholders to ensure data science solutions are well aligned to product and business needs.
- Work with ML Engineers to support deployment, monitoring, and performance tracking of your models.
- Contribute to team standards on reproducibility, documentation, and model evaluation.
- Apply responsible AI practices to ensure fairness and transparency.
- Take part in peer reviews, knowledge sharing, and internal learning sessions.
- Support and coach junior team members and peers, contributing to their growth.
- Play an active role in shaping our data science culture and community.
Requirements
Must Have
- Experience delivering machine learning or advanced analytics solutions with measurable impact.
- Proficient in Python and SQL, with practical experience in modelling, feature engineering, and evaluation.
- Strong problem‑solving skills and ability to break down complex problems into data‑driven approaches.
- Comfortable working collaboratively in cross‑functional teams.
- Clear communicator with a passion for sharing insights and learning from others.
- Background in a quantitative discipline (e.g. Computer Science, Mathematics, Statistics, Engineering) or equivalent hands‑on experience in applied machine learning.
Nice to Have
- Experience working in regulated sectors such as insurance, banking, or financial services.
- Familiarity with tools like MLflow, model registries, or experimentation platforms.
- Understanding of basic CI/CD concepts or exposure to production ML workflows.
- Interest in generative AI or large language models (e.g. OpenAI, Vertex AI).
- Awareness of responsible AI principles, such as fairness or explainability in models.
Benefits
We’re a business built for pace and performance. Here, you’ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress. We believe diverse teams make better decisions, and we’re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
Data Scientist employer: Compare the Market
As a Data Scientist at our London-based hybrid workplace, you'll thrive in a dynamic environment that champions innovation and collaboration. We offer a culture that values diverse perspectives, providing ample opportunities for professional growth and development while ensuring that your contributions have a meaningful impact on our business. Join us to be part of a team that not only embraces cutting-edge technology but also prioritises responsible AI practices and fosters an inclusive atmosphere where every voice is heard.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Network Like a Pro
Get out there and connect with people in the data science field! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the industry. Building relationships can lead to job opportunities that aren’t even advertised!
✨Show Off Your Skills
Create a portfolio showcasing your machine learning projects. Use GitHub to share your code and document your thought process. This not only demonstrates your technical skills but also your ability to communicate complex ideas clearly.
✨Ace the Interview
Prepare for interviews by practising common data science questions and case studies. Don’t forget to brush up on your Python and SQL skills! We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Apply Through Our Website
When you find a role that excites you, apply directly through our website! It shows your enthusiasm and gives us a chance to see your application in the best light. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with machine learning, Python, and SQL, and don’t forget to showcase any projects that had a measurable impact!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain how your skills align with our needs, especially in translating business challenges into data science problems. Keep it engaging and personal.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled complex problems using data-driven approaches. We love seeing clear communication about your thought process and the outcomes of your work.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Compare the Market
✨Know Your Stuff
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss specific projects where you've built predictive models or conducted statistical analyses. This will show that you can translate business challenges into data science solutions effectively.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex problems in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will help you demonstrate your ability to break down challenges and apply data-driven approaches.
✨Communicate Clearly
As a Data Scientist, you'll need to collaborate with various stakeholders. Practice explaining your technical work in simple terms. This will not only showcase your communication skills but also your passion for sharing insights and learning from others.
✨Embrace Collaboration
Be ready to discuss your experience working in cross-functional teams. Highlight any instances where you've supported junior team members or contributed to team standards. This shows that you're not just a lone wolf but someone who values teamwork and community.
