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- Tasks: Design and deploy advanced ML and GenAI solutions in secure environments.
- Company: Leading tech firm at the forefront of AI and machine learning.
- Benefits: Competitive salary, bonus, hybrid work, and opportunities for professional growth.
- Other info: Collaborative environment with leadership potential and innovative projects.
- Why this job: Join a dynamic team and make an impact with cutting-edge technology.
- Qualifications: 3+ years in Data Science, strong Python skills, and active DV clearance required.
The predicted salary is between 75000 - 75000 £ per year.
DV Cleared Data Scientist
Location: London (Hybrid)
Salary: Up to £75,000 base + bonus
We’re hiring a DV-Cleared Data Scientist to work at the cutting edge of AI, machine learning, and large-scale data systems within highly secure environments. This is a hands-on, delivery-focused role where you’ll design, build, and deploy advanced ML and GenAI solutions while acting as a technical leader on client engagements.
NOTE: You MUST hold active UK DV (Developed Vetting) Security Clearance to be considered. Applications without active DV clearance unfortunately cannot be progressed.
What You’ll Be Doing:
- Designing and deploying machine learning models and large models (LLMs) in cloud and secure HPC environments
- Leading day-to-day technical delivery across projects and mentoring junior team members
- Acting as a subject matter expert across ML, AI architecture, and GenAI advancements
- Building scalable, production-grade data science solutions
- Working closely with stakeholders to translate complex requirements into technical solutions
- Driving innovation by staying current with emerging AI/ML trends and technologies
Essential Criteria:
- 3+ years of commercial Data Science experience
- Strong programming expertise in Python
- Experience with ML/AI systems, including at least one of: Agentic AI systems and architectures, Retrieval-Augmented (RAG, Graph RAG), Computer Vision / Vision Models, Audio processing
- Hands-on experience with Docker, Linux/Unix, Git, and testing frameworks
- Experience working with AWS or Azure
- Understanding of data governance and security best practices
- Proven ability to communicate complex technical concepts to non-technical stakeholders
Desirable:
- Experience working with GPUs in cloud environments
- Familiarity with ML model monitoring and observability
- API development experience
- Exposure to CI/CD pipelines and DevOps practices
- Knowledge of data engineering principles
What Sets You Apart:
- Strong analytical and critical thinking skills
- Ability to operate in client-facing environments and manage stakeholders effectively
- Comfortable working across a broad tech stack and integrating multiple systems
- A collaborative mindset with leadership potential
If you are a DV-cleared Data Scientist ready to lead cutting-edge AI solutions in secure environments, apply today.
Data Scientist in City of London employer: Energy Jobline ZR
Contact Detail:
Energy Jobline ZR Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who work in secure environments. They might have insider info on job openings or can even refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving AI and machine learning. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, ML systems, and how you’ve tackled complex problems in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Data Scientist in City of London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming expertise in Python and any experience with ML/AI systems. We want to see how your skills align with the role, so don’t hold back on showcasing your best projects!
Tailor Your Application: Take a moment to customise your application for this specific role. Mention your experience with cloud environments like AWS or Azure, and how you’ve tackled complex data science challenges. This helps us see why you’re the perfect fit!
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your experience and avoid jargon unless it’s relevant. We appreciate clarity, especially when it comes to technical concepts!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the easiest way for us to receive your details and ensures you’re considered for the role. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Stuff
Make sure you brush up on your technical skills, especially in Python and machine learning. Be ready to discuss your experience with AI systems and how you've applied them in real-world scenarios. This is your chance to showcase your expertise!
✨Showcase Your Leadership Skills
Since this role involves mentoring junior team members and leading projects, think of examples where you've taken charge or guided others. Prepare to share how you’ve effectively communicated complex concepts to non-technical stakeholders.
✨Stay Current with Trends
Demonstrate your passion for the field by discussing recent advancements in AI and machine learning. Mention any new technologies or methodologies you've explored and how they could benefit the company. This shows you're proactive and innovative!
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving abilities in client-facing situations. Think about challenges you've faced in previous roles and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers.