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- Tasks: Bridge data science innovation with enterprise deployment and work on cutting-edge ML technologies.
- Company: Leading global tech consultancy with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Shape the future of AI while collaborating with Fortune 500 technical leaders.
- Qualifications: CS/Data Science degree or equivalent experience with 4+ years in data science.
- Other info: Dynamic environment with a focus on mentorship and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
Full-Stack Data Scientist | Sr. Associate/ManagerLeading Global Tech Consultancy
THE OPPORTUNITY Bridge data science innovation with enterprise deployment. Work with cutting-edge ML technologies while ensuring scalable production systems for our global client base.
WHAT YOU\’LL DO ✅ Deploy ML models as microservices using AWS (SageMaker, Bedrock, Glue) ✅ Build secure APIs with Apigee for enterprise AI access ✅ Manage complete MLOps lifecycle: training → monitoring → drift detection ✅ Develop CI/CD pipelines and mentor client teams ✅ Work directly with Fortune 500 technical leaders
TECH STACK Python • R • TensorFlow • PyTorch • Hugging Face • AWS • Docker • Kubernetes • Jenkins • Apigee
REQUIREMENTS 🎓 CS/Data Science degree or equivalent experience 💼 4+ years data science with production deployment track record ⚙️ Advanced Python/R and complete MLOps experience 💬 Excellent communication and client management skills
IDEAL CANDIDATE You\’re a technical innovator who thrives at the intersection of ML research and production engineering. You excel at translating complex AI concepts and have proven experience deploying scalable ML solutions in enterprise environments.
Ready to shape the future of AI? Join our world-class team!
- APPLY NOW 👇 📧 DM me or email: gillian.shields@codeverse.co.uk 🔗 Share with your network if you know someone perfect for this role!
Full Stack Data Scientist employer: CodeVerse
Contact Detail:
CodeVerse Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Full Stack Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML models and APIs. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts simply, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Full Stack Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Full Stack Data Scientist role. Highlight your MLOps experience and any projects where you've deployed ML models, as this will catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your background aligns with our tech stack. Share specific examples of your work with AWS or CI/CD pipelines to show us what you can bring to the table.
Showcase Your Communication Skills: Since client management is key in this role, make sure your application demonstrates your ability to communicate complex ideas clearly. Use straightforward language and avoid jargon where possible to keep it relatable.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at CodeVerse
✨Know Your Tech Stack
Make sure you’re well-versed in the tech stack mentioned in the job description. Brush up on Python, R, TensorFlow, and AWS services like SageMaker and Glue. Being able to discuss your hands-on experience with these tools will show that you’re ready to hit the ground running.
✨Showcase Your MLOps Experience
Prepare to talk about your experience managing the complete MLOps lifecycle. Be ready to share specific examples of how you've deployed ML models, monitored their performance, and handled drift detection. This will demonstrate your practical knowledge and problem-solving skills.
✨Communicate Clearly
Since excellent communication is key for this role, practice explaining complex AI concepts in simple terms. Think about how you would explain your projects to a non-technical audience. This will not only help you in the interview but also in your future client interactions.
✨Prepare Questions for Them
Have a few insightful questions ready to ask your interviewers. This could be about their current projects, team dynamics, or how they envision the future of AI in their consultancy. It shows your genuine interest in the role and helps you assess if it’s the right fit for you.
