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- Tasks: Lead a team of Data Scientists to create innovative analytic solutions.
- Company: Join a dynamic company shaping the future of underwriting and pricing.
- Benefits: Enjoy a collaborative environment with opportunities for growth and impact.
- Why this job: Be at the forefront of data science, influencing core business strategies.
- Qualifications: 7+ years in data science or actuarial roles with strong leadership skills.
- Other info: Contact tilly.martin-redman@eamesconsulting.com for more details.
The predicted salary is between 43200 - 72000 £ per year.
Our client is looking for a forward thinking Data Scientist to lead and grow their capability, helping shape the future of underwriting and pricing in a dynamic and collaborative environment.
You will be leading a team of Data Scientists to deliver impactful analytic solutions, help define and deliver strategic data initiatives and partner with the wider business to integrate data science into core business platforms.
The ideal candidate will have strong leadership and stakeholder experience and 7+ years in a data science or actuarial role.
For more information please reach out: tilly.martin-redman@eamesconsulting.com
Data Science Manager employer: Eames Consulting
Contact Detail:
Eames Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Manager
✨Tip Number 1
Showcase your leadership skills by discussing any previous experience where you've successfully managed a team or project. Highlight how you motivated your team and the impact of your leadership on project outcomes.
✨Tip Number 2
Familiarise yourself with the latest trends in data science and underwriting. Being able to discuss current methodologies and technologies during your conversations will demonstrate your passion and knowledge in the field.
✨Tip Number 3
Network with professionals in the data science and actuarial fields. Attend industry events or webinars to connect with potential colleagues and learn more about the company culture, which can give you an edge in interviews.
✨Tip Number 4
Prepare to discuss how you would integrate data science into core business platforms. Think about specific examples from your past work that illustrate your ability to align data initiatives with business goals.
We think you need these skills to ace Data Science Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your leadership experience and relevant skills in data science. Focus on your achievements in previous roles, especially those that demonstrate your ability to lead teams and deliver impactful analytic solutions.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the job requirements, particularly your experience in underwriting and pricing, and your vision for integrating data science into business platforms.
Showcase Relevant Projects: Include specific examples of projects you've led or contributed to that are relevant to the role. Highlight any strategic data initiatives you have been part of and the outcomes achieved, as this will demonstrate your capability to shape the future of data science in the company.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial in a managerial role.
How to prepare for a job interview at Eames Consulting
✨Showcase Your Leadership Skills
As a Data Science Manager, you'll be leading a team. Be prepared to discuss your leadership style and provide examples of how you've successfully managed teams in the past. Highlight any experiences where you’ve mentored others or driven projects to completion.
✨Demonstrate Technical Expertise
With over 7 years in data science or actuarial roles, you should be ready to dive deep into technical discussions. Brush up on key data science concepts, tools, and methodologies relevant to the role, and be prepared to explain how you've applied them in real-world scenarios.
✨Prepare for Stakeholder Engagement
This role requires strong stakeholder experience. Think about times when you've collaborated with different departments or influenced decision-making. Be ready to share how you effectively communicate complex data insights to non-technical stakeholders.
✨Align with Business Goals
Understand the company's vision and how data science can drive their strategic initiatives. Be prepared to discuss how you would integrate data science into core business platforms and contribute to the overall success of the organisation.
