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For Companies At a Glance
- Tasks: Lead the design of data infrastructure and deploy ML models for impactful analytics.
- Company: Join a forward-thinking company in Worcester, driving innovation in data science.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a collaborative culture that values creativity and technical excellence.
- Qualifications: Significant experience in Data Science or ML Engineering with strong Python skills required.
- Other info: Bonus points for experience in insurance or financial services and familiarity with Docker.
The predicted salary is between 54000 - 84000 £ per year.
Key Responsibilities:
- Lead the design and implementation of scalable data infrastructure for machine learning, analytics, and reporting.
- Develop and launch secure APIs and DaaS solutions.
- Deploy production-ready ML models and manage their lifecycle.
- Promote data governance and quality standards across the platform.
- Collaborate with cross-functional teams to translate business challenges into technical solutions.
Tech Stack Includes: Python, SQL, Azure, Postgres, Langchain, Ollama, Polars, GitLab CI/CD, Systemd, Ansible
Ideal Candidate Profile:
- Significant experience as a Data Science or ML Engineer, with leadership responsibilities.
- Strong Python skills and experience with cloud-based data platforms (preferably Azure).
- Proven success deploying ML models into production.
- Solid understanding of data privacy, governance, and API development.
- Excellent communication skills and stakeholder engagement abilities.
Bonus Points For:
- Experience in insurance or financial services.
- Familiarity with Docker, Kubernetes, or infrastructure-as-code tools.
Lead Data Science Engineer in Worcester employer: FBI &TMT
Contact Detail:
FBI &TMT Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Science Engineer in Worcester
✨Tip Number 1
Familiarise yourself with the specific tech stack mentioned in the job description. Brush up on your Python and SQL skills, and make sure you understand how to work with Azure and Postgres, as these are crucial for the role.
✨Tip Number 2
Showcase your leadership experience in data science or ML projects. Be prepared to discuss specific instances where you've led a team or project, particularly focusing on how you managed the deployment of ML models into production.
✨Tip Number 3
Highlight your understanding of data governance and privacy standards. Be ready to discuss how you've implemented these practices in previous roles, as this will demonstrate your commitment to quality and compliance.
✨Tip Number 4
If you have experience in the insurance or financial services sectors, make sure to mention it. This could give you an edge over other candidates, so prepare examples of how your background aligns with the industry.
We think you need these skills to ace Lead Data Science Engineer in Worcester
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, explain how your background aligns with the key responsibilities of the role. Mention specific projects where you've deployed ML models and how you’ve promoted data governance in previous positions.
Showcase Relevant Skills: Clearly list your technical skills relevant to the job description, such as API development, SQL, and experience with tools like GitLab CI/CD. If you have bonus skills like Docker or Kubernetes, make sure to include those too!
Highlight Collaboration Experience: Since the role involves working with cross-functional teams, provide examples of how you've successfully collaborated with others to solve business challenges. Strong communication skills are key, so illustrate this in your application.
How to prepare for a job interview at FBI &TMT
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and Azure in detail. Highlight specific projects where you've implemented scalable data infrastructure or deployed ML models, as this will demonstrate your hands-on expertise.
✨Understand the Business Context
Research the company and its industry, especially if they operate in insurance or financial services. Be ready to explain how your technical solutions can address their specific business challenges, showcasing your ability to translate technical jargon into business value.
✨Emphasise Leadership Experience
Since the role involves leadership responsibilities, prepare examples of how you've led teams or projects in the past. Discuss your approach to promoting data governance and quality standards, as well as how you engage stakeholders effectively.
✨Prepare for Technical Questions
Expect questions about deploying production-ready ML models and managing their lifecycle. Brush up on your knowledge of APIs and DaaS solutions, and be ready to discuss any relevant tools like Docker or Kubernetes, even if they're just bonus points.
