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- Tasks: Build predictive models and collaborate with ML Engineers to drive business growth.
- Company: Join Policy Expert, a top-rated insurer transforming the industry with innovative technology.
- Benefits: Enjoy hybrid work, generous pension matching, private medical cover, and a £1,000 learning budget.
- Why this job: Be part of a dynamic team using cutting-edge data science to impact customer experience positively.
- Qualifications: Experience in machine learning, Python programming, and a knack for solving real-world problems.
- Other info: We value diversity and are committed to providing equal opportunities for all applicants.
The predicted salary is between 36000 - 60000 £ per year.
Data ScientistPolicy Expert is a forward‐thinking insurer that uses proprietary technology and data to deliver reliable products and a strong customer experience. We operate across Home, Motor and Pet insurance and are rapidly expanding our data science capabilities.
ResponsibilitiesAs a Data Scientist you will:
Build predictive statistical and machine learning models, and develop pipelines to drive business growth.
Collaborate with ML Engineers to deploy models into production and ensure ongoing value.
Translate business problems into technical solutions and communicate outcomes to stakeholders.
Define and prioritise data science initiatives using data to quantify opportunities.
Design and monitor A/B tests to measure impact of initiatives.
Advocate the value of data science and ML across the organization.
Qualifications
Experience designing and building data products with large datasets, and understanding deployment in production.
Applied knowledge of statistics and machine learning with demonstrable business impact.
Proactive, self‐starter who can unblock obstacles.
Product‐mindset focused on business outcomes.
Familiarity with MLOps principles and, ideally, GenAI solutions.
Strong communication skills, able to explain technical concepts to non‐technical audiences.
Proficiency in Python, SQL, and experience querying large datasets.
Knowledge of best coding practices and efficient, optimised code.
Experience with GCP Vertex AI, or similar cloud services, is a plus.
Knowledge of the insurance industry is advantageous but not required.
BenefitsLocation: London office (50/50 hybrid). We offer:
- Pension contribution match up to 7%
- Private medical & dental cover
- Learning budget of £1,000 per year + study leave
- Enhanced maternity & paternity benefits
- Travel season ticket loan
- Access to London events & private lounge
- Employee wellbeing programme
- Prayer room in office.
Equal OpportunityWe pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit solely on skills, knowledge, and experience. If you require reasonable adjustments during the interview process, please let us know.
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Data Scientist employer: Policy Expert
Contact Detail:
Policy Expert Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarise yourself with the insurance industry, even if it's not essential. Understanding the nuances of this sector can help you tailor your discussions and demonstrate how your data science skills can directly impact their business.
✨Tip Number 2
Showcase your experience with machine learning models and real-time ML engineering techniques. Be prepared to discuss specific projects where you've successfully deployed models into production, as this will resonate well with the team at Policy Expert.
✨Tip Number 3
Highlight your ability to work collaboratively within cross-functional teams. Prepare examples of how you've effectively communicated complex data science concepts to non-technical stakeholders, as this is crucial for the role.
✨Tip Number 4
If you have experience with GCP Vertex AI or similar services, make sure to mention it. This knowledge can set you apart from other candidates and show that you're ready to hit the ground running in their tech environment.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, machine learning, and programming skills, particularly in Python and SQL. Use specific examples to demonstrate your ability to build and deploy models.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for transforming the insurance industry with data science. Mention how your skills align with Policy Expert's goals and your understanding of their customer-centric approach.
Showcase Your Projects: If you have worked on any relevant projects, especially those involving machine learning or GenAI, be sure to include them in your application. Describe the challenges you faced and how you overcame them using data-driven solutions.
Prepare for Technical Questions: Anticipate technical questions related to data science and machine learning during the interview process. Brush up on your knowledge of statistical models, A/B testing, and data cleansing techniques to demonstrate your expertise.
How to prepare for a job interview at Policy Expert
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning models and how you've deployed them in production. Highlight your programming skills in Python and SQL, and be ready to provide examples of how you've used these tools to solve real-world problems.
✨Understand the Business Context
Demonstrate your ability to translate complex data science concepts into practical solutions for business problems. Research Policy Expert's goals and challenges in the insurance industry, and think about how your skills can contribute to their growth.
✨Prepare for Team Collaboration Questions
Since you'll be working within a cross-functional team, be ready to discuss your experiences collaborating with product managers, ML engineers, and analysts. Share examples of how you've effectively communicated technical information to non-technical stakeholders.
✨Emphasise Your Problem-Solving Approach
Be prepared to talk about your approach to developing data science solutions and how you monitor their effectiveness. Discuss any A/B testing you've conducted and how you've used data to quantify new opportunities for business growth.