At a Glance
- Tasks: Bridge data science innovation with enterprise deployment and work with cutting-edge ML technologies.
- Company: Leading global tech consultancy focused on innovative solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Shape the future of AI while working with Fortune 500 companies.
- Qualifications: CS/Data Science degree or equivalent experience with 4+ years in data science.
- Other info: Join a world-class team and mentor client teams in a dynamic environment.
The predicted salary is between 36000 - 60000 Β£ 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\βLL DO β Deploy ML models as microservices using AWS (SageMaker, Bedrock, Glue) β Build secure APIs with Apigee for enterprise AI access β Manage complete MLOps lifecycle: training β monitoring β drift detection β Develop CI/CD pipelines and mentor client teams β Work directly with Fortune 500 technical leaders
TECH STACK Python β’ R β’ TensorFlow β’ PyTorch β’ Hugging Face β’ AWS β’ Docker β’ Kubernetes β’ Jenkins β’ Apigee
REQUIREMENTS π CS/Data Science degree or equivalent experience πΌ 4+ years data science with production deployment track record βοΈ Advanced Python/R and complete MLOps experience π¬ Excellent communication and client management skills
IDEAL CANDIDATE You\βre 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 π π§ DM me or email: gillian.shields@codeverse.co.uk π 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 π€«
We think this is how you could land Full Stack Data Scientist
β¨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes itβs not just what you know, but who you know that can land you that dream job.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML models and APIs. We want to see your work in action, so make it easy for potential employers to see what you can do.
β¨Tip Number 3
Prepare for interviews by brushing up on your technical skills and practising common data science questions. We recommend doing mock interviews with friends or using online platforms to get comfortable with the process.
β¨Tip Number 4
Donβt forget to apply through our website! Itβs the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Full Stack Data Scientist
Some tips for your application π«‘
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Full Stack Data Scientist role. Highlight your experience with ML technologies, Python, and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this position. Share specific examples of how you've deployed ML models or managed MLOps lifecycles in the past.
Showcase Your Communication Skills: Since excellent communication is key, make sure your application clearly conveys your thoughts. Use straightforward language and structure your ideas logically to demonstrate your client management skills.
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 donβt miss out on any important updates!
How to prepare for a job interview at CodeVerse
β¨Know Your Tech Stack
Make sure youβre 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 youβre ready to hit the ground running.
β¨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.
β¨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 help you connect with interviewers and showcase your client management skills.
β¨Prepare Questions for Them
Have a few insightful questions ready to ask your interviewers. Inquire about their current projects, team dynamics, or how they envision the future of AI in their consultancy. This shows your genuine interest in the role and helps you assess if itβs the right fit for you.