At a Glance
- Tasks: Lead a team to develop analytics solutions that drive business performance.
- Company: Global insurance business with a focus on strategic analytics.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Join a dynamic team in a growing field with excellent career prospects.
- Why this job: Shape impactful analytics solutions in a hands-on leadership role.
- Qualifications: Experience in data science, predictive modelling, and stakeholder engagement.
The predicted salary is between 100000 - 110000 £ per year.
Salary: £100,000 - 110,000 per year
Requirements
- Experience across Data Science, Predictive Modelling and Advanced Analytics
- Ideally experience within Insurance, London Market or Claims environments
- Broader Financial Services experience will also be considered
Responsibilities
- Identify opportunities where data can improve performance
- Work closely with senior stakeholders to understand business challenges
- Develop analytics-led solutions that deliver real value
- Oversee the development of predictive models and machine learning solutions
- Provide leadership and support to a team of Data Scientists
- Act as a key link between the business and analytics functions
- Combine strong technical knowledge with stakeholder engagement, mentoring and project delivery
Technologies
- Support
- Machine Learning
We are a global insurance business with a growing Strategic Analytics team focused on using predictive modelling and advanced analytics to drive better business decisions. This is a Data Science Manager role based in London on a hybrid working arrangement of 2-3 days per week, offering a salary of £100,000 to £110,000. You will join a hands-on leadership role where you will help shape analytics solutions that create measurable business value.
Data Science Manager in London employer: Sivara GmbH
As a leading global insurance business, we pride ourselves on fostering a dynamic work culture that values innovation and collaboration. Our London-based Strategic Analytics team offers exceptional opportunities for professional growth, with a focus on mentorship and hands-on leadership in the field of data science. Enjoy a competitive salary, hybrid working arrangements, and the chance to make a significant impact through analytics-led solutions that drive real business value.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager in London
✨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 Sivara GmbH!
✨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 Science Manager at Sivara GmbH.
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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 Sivara GmbH.
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We think you need these skills to ace Data Science Manager in London
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 Sivara GmbH, 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 Sivara GmbH. 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 Sivara GmbH
✨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 Sivara GmbH!
✨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.
