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For Companies At a Glance
- Tasks: Lead the design of data infrastructure and deploy ML models.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Enjoy flexible work options and a collaborative team environment.
- Why this job: Make an impact by solving real business challenges with cutting-edge technology.
- Qualifications: Experience in Data Science or ML Engineering with strong Python skills required.
- Other info: Bonus for experience in insurance or financial services.
The predicted salary is between 48000 - 84000 £ per year.
Job Description
Key Responsibilities:
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Lead the design and implementation of scalable data infrastructure for machine learning, analytics, and reporting.
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Develop and launch secure APIs and DaaS solutions.
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Deploy production-ready ML models and manage their lifecycle.
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Promote data governance and quality standards across the platform.
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Collaborate with cross-functional teams to translate business challenges into technical …
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Lead Data Science Engineer employer: FBI &TMT
Contact Detail:
FBI &TMT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Science Engineer
✨Tip Number 1
Familiarise yourself with our tech stack, especially Python and Azure. Brush up on your skills by working on personal projects or contributing to open-source projects that utilise these technologies.
✨Tip Number 2
Showcase your leadership experience in data science or ML engineering. Prepare examples of how you've led projects or teams, focusing on the impact of your contributions.
✨Tip Number 3
Network with professionals in the data science field, particularly those with experience in insurance or financial services. Attend relevant meetups or webinars to make connections and learn about industry trends.
✨Tip Number 4
Demonstrate your understanding of data governance and API development. Be ready to discuss best practices and any relevant experiences you have in ensuring data quality and security.
We think you need these skills to ace Lead Data Science Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as a Data Science or ML Engineer, especially any leadership roles. Emphasise your strong Python skills and familiarity with cloud-based platforms like Azure.
Craft a Compelling Cover Letter: In your cover letter, discuss your experience deploying ML models into production and your understanding of data privacy and governance. Use specific examples to demonstrate your problem-solving skills and how you've translated business challenges into technical solutions.
Showcase Relevant Projects: If you have worked on projects involving APIs, DaaS solutions, or data infrastructure, be sure to include these in your application. Highlight your role in these projects and the impact they had on the organisation.
Prepare for Technical Questions: Be ready to discuss your technical expertise during interviews. Brush up on your knowledge of the tech stack mentioned in the job description, including Python, SQL, and Azure, as well as any experience with Docker or Kubernetes.
How to prepare for a job interview at FBI &TMT
✨Showcase Your Leadership Experience
As a Lead Data Science Engineer, demonstrating your leadership skills is crucial. Be prepared to discuss specific instances where you've led projects or teams, highlighting your ability to guide others and make impactful decisions.
✨Demonstrate Technical Proficiency
Make sure to brush up on your Python and cloud-based data platform skills, especially Azure. Be ready to answer technical questions and possibly solve problems on the spot to showcase your expertise in the tech stack mentioned.
✨Discuss Data Governance Knowledge
Since data governance is a key responsibility, be prepared to talk about your understanding of data privacy and quality standards. Share examples of how you've implemented these practices in previous roles to ensure data integrity.
✨Prepare for Cross-Functional Collaboration
Collaboration is essential in this role. Think of examples where you've worked with different teams to solve business challenges. Highlight your communication skills and how you effectively engaged stakeholders to achieve project goals.
