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- Tasks: Develop AI applications to create personalized experiences and solve real-world problems.
- Company: Join Compare the Market, a mission-driven company focused on simplifying financial decision-making.
- Benefits: Enjoy hybrid working, generous holidays, private healthcare, and paid development days.
- Why this job: Be part of a collaborative team that drives meaningful results and impacts lives.
- Qualifications: Passion for data science, experience in AI model development, and strong skills in Python and SQL.
- Other info: You'll have autonomy to drive your career with support from talented colleagues.
The predicted salary is between 28800 - 48000 £ per year.
Our purpose is to make great financial decision making a breeze for everyone, and that purpose drives us every day. It’s why we’re on a mission to create an automated quoting engine, with the simplest of experiences, wrapped in a brand everyone loves! We change lives by making it simple to switch and save money and that’s why good things happen when you meerkat.
We’d love you to be part of our journey.
As a Data Scientist at Compare the Market you’ll be developing the Data Science and AI applications that will help us to deliver our company mission. You’ll work on existing and new products to create personalised experiences and create impactful, real-world solutions for customers, colleagues and partners. This is a hands-on, collaborative role where you’ll take projects from idea to implementation, driving meaningful results across the business.
Some of the great things you’ll be doing:
- Solve Real-World Problems: work with a range of teams and stakeholders to design data science applications that address real-world problems.
- End-to-End Model Development: scope and manage the development of models, from ideation to production, ensuring that results deliver tangible impact and ethical outcomes.
- Collaborate for Success: partner with Machine Learning Engineers to deploy models into production and optimise their performance.
- Drive Decision-Making: present technical insights and proposals in an engaging, impactful way to senior leadership.
What we’d like to see from you:
You don’t need to tick every box, but here’s what will set you up for success:
- Passion: a strong motivation to use data science to solve real-world customer problems.
- Expertise: demonstrable experience in end-to-end AI and machine learning model development.
- Technical Skills: strong proficiency in Python, SQL and statistics.
- Curiosity: naturally curious and eager to learn, with a hunger to explore new ideas.
- Focus on Outcomes: results-driven with a keen ability to measure success.
- Communication Skills: adept at explaining complex technical results to non-technical audiences in a clear and impactful way.
We’re a place of opportunity. You’ll have the tools and autonomy to drive your own career, supported by a team of amazingly talented people.
And then there’s our benefits. For us, it’s not just about a competitive salary and hybrid working, we care about what matters to you. From a generous holiday allowance and private healthcare to an electric car scheme and paid development, wellbeing and CSR days, we’ve got you covered!
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Data Scientist employer: Compare the Market
Contact Detail:
Compare the Market Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Show your passion for data science by discussing real-world problems you've solved in previous roles. Highlight specific examples where your work made a tangible impact, as this aligns perfectly with our mission.
✨Tip Number 2
Familiarize yourself with our products and the financial decision-making process. Understanding how your role as a Data Scientist can enhance customer experiences will help you stand out during discussions.
✨Tip Number 3
Prepare to discuss your experience with end-to-end model development. Be ready to explain your approach to scoping, managing, and deploying models, as well as how you ensure ethical outcomes.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Being able to communicate effectively with non-technical stakeholders is crucial, so think of ways to make your insights engaging and impactful.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Company Mission: Before applying, take some time to understand Compare the Market's mission and values. Tailor your application to reflect how your skills and experiences align with their goal of making financial decision-making easier for everyone.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in end-to-end AI and machine learning model development. Provide specific examples of projects where you solved real-world problems using data science.
Showcase Technical Skills: Make sure to clearly list your technical skills, particularly in Python, SQL, and statistics. Mention any relevant tools or frameworks you have used in your previous work that would be beneficial for this role.
Communicate Effectively: When writing your application, focus on how you can explain complex technical concepts to non-technical audiences. Use clear and impactful language to demonstrate your communication skills, as this is crucial for the role.
How to prepare for a job interview at Compare the Market
✨Show Your Passion for Data Science
Make sure to express your enthusiasm for using data science to solve real-world problems. Share specific examples of how you've applied your skills to create impactful solutions in previous roles.
✨Demonstrate End-to-End Model Development Experience
Be prepared to discuss your experience with the entire lifecycle of AI and machine learning model development. Highlight projects where you took models from ideation to production, focusing on the tangible impacts they had.
✨Communicate Complex Ideas Simply
Practice explaining technical concepts in a way that non-technical stakeholders can understand. Use clear, engaging language and be ready to present insights that drive decision-making effectively.
✨Emphasize Collaboration Skills
Since this role involves working closely with Machine Learning Engineers and other teams, share examples of successful collaborations. Highlight how you contributed to team success and drove meaningful results together.
