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For Companies At a Glance
- Tasks: Lead the development of scalable data platforms and mentor a dynamic team.
- Company: Join a tech-driven leader in the insurance software industry.
- Benefits: Enjoy flexible work options and a culture that values innovation and inclusion.
- Why this job: Be at the forefront of data transformation with a focus on technical excellence.
- Qualifications: Extensive experience in data science, ML engineering, or data platform engineering required.
- Other info: Ideal for those passionate about cloud technologies and mentoring others.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
Our client, a technology-driven leader in the insurance software space, is seeking a Technical Lead – Data Science & Engineering to help architect and scale their unified data platform and Data-as-a-Service (DaaS) capabilities.
This is a hands-on leadership role ideal for someone who thrives at the intersection of data engineering, machine learning, and modern cloud infrastructure. You'll provide t…
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Data Technical Lead employer: FBI &TMT
Contact Detail:
FBI &TMT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Technical Lead
✨Tip Number 1
Familiarise yourself with the latest trends in data engineering and machine learning. Being well-versed in current technologies and methodologies will not only boost your confidence but also demonstrate your commitment to staying ahead in this rapidly evolving field.
✨Tip Number 2
Network with professionals in the insurance and technology sectors. Attend industry events, webinars, or meetups to connect with potential colleagues and learn about their experiences. This can provide valuable insights and may even lead to referrals.
✨Tip Number 3
Showcase your leadership skills by sharing examples of how you've successfully mentored teams or led projects in the past. Highlighting your ability to guide others and foster collaboration will make you stand out as a candidate who can thrive in a hands-on leadership role.
✨Tip Number 4
Research the company’s existing data platforms and DaaS capabilities. Understanding their current infrastructure and challenges will allow you to tailor your discussions during interviews, demonstrating your proactive approach and genuine interest in contributing to their success.
We think you need these skills to ace Data Technical Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, ML engineering, and data platform engineering. Emphasise any leadership roles you've held and specific projects that demonstrate your ability to architect scalable data platforms.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data transformation and innovation. Mention how your background aligns with the company's goals and how you can contribute to their Data-as-a-Service capabilities.
Showcase Relevant Projects: Include examples of large-scale data systems you've delivered, particularly those using cloud platforms like AWS, Azure, or GCP. Highlight your experience with MLOps practices and any tools you've introduced that improved performance.
Prepare for Technical Questions: Anticipate technical questions related to data architecture, ML workflows, and cloud infrastructure. Be ready to discuss your approach to mentoring teams and engaging stakeholders effectively.
How to prepare for a job interview at FBI &TMT
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with data platforms and cloud technologies. Highlight specific projects where you've led the architecture or development of scalable systems, especially in AWS, Azure, or GCP.
✨Demonstrate Leadership Skills
Since this role involves mentoring a team, share examples of how you've guided engineers and data scientists in previous roles. Discuss your approach to fostering collaboration and promoting best practices in data engineering and ML workflows.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in deploying ML models or building DaaS solutions, and be ready to explain how you overcame them.
✨Engage with Stakeholders
This role requires strong stakeholder engagement. Be ready to discuss how you've collaborated with cross-functional teams in the past. Emphasise your communication skills and ability to translate technical concepts to non-technical stakeholders.
