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For Companies At a Glance
- Tasks: Design and develop data solutions for advanced analytics and machine learning applications.
- Company: Join a leading organisation focused on innovative data-driven solutions.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact by solving complex problems with cutting-edge technology in a collaborative environment.
- Qualifications: Must have active DV Clearance, strong data science skills, and proficiency in Python and ML tools.
- Other info: This role is exclusively for sole British nationals.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
Please note, you must hold active DV Clearance and be a sole British national to be eligible for this role.
Responsibilities:
- Design, develop, and test solutions to collect, integrate, and prepare data for advanced analytics and machine learning applications.
- Analyse complex datasets to uncover trends, patterns, and actionable insights that drive business or operational outcomes.
- Build, prototype, and evaluate statistical and machine learning models to solve real-world problems, testing feasibility and estimating impact before full deployment.
- Engineer and implement ML-based solutions, owning the full life cycle – from model development and deployment to monitoring and iteration.
- Deploy models into production environments, handling the integration and operationalisation of ML within wider systems and applications.
- Continuously evaluate and monitor model performance, identifying degradation, performance gaps, or opportunities for optimisation.
- Collaborate closely with data analysts, engineers, and other stakeholders to define new tools, enhance workflows, and support innovation across teams.
About You:
- You have a strong foundation in data science, analytics, or machine learning, with hands-on experience developing models that solve practical problems and deliver measurable impact.
- You are comfortable working across the full machine learning life cycle – from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring.
- You are proficient in Python and its data/ML ecosystem (eg pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings.
- You have deployed models into live systems and understand how to make ML operational – whether that means working with APIs, integrating into existing applications, or using containerisation tools like Docker
DV Cleared Data Scientist employer: Korn Ferry
Contact Detail:
Korn Ferry Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land DV Cleared Data Scientist
✨Tip Number 1
Make sure to highlight your active DV Clearance in any conversations or networking opportunities. This is a crucial requirement for the role, and mentioning it upfront can set you apart from other candidates.
✨Tip Number 2
Familiarise yourself with the latest trends and technologies in machine learning and data science. Being able to discuss recent advancements or tools you've used can demonstrate your passion and expertise during interviews.
✨Tip Number 3
Prepare to discuss specific projects where you've deployed machine learning models into production. Be ready to explain the challenges you faced and how you overcame them, as this will showcase your practical experience.
✨Tip Number 4
Network with professionals in the data science field, especially those who have experience in government or security sectors. They can provide insights into the role and may even refer you to opportunities within their organisations.
We think you need these skills to ace DV Cleared Data Scientist
Some tips for your application 🫡
Highlight Your Clearance: Since active DV Clearance is a requirement for this role, make sure to prominently mention your clearance status in your CV and cover letter. This will immediately show that you meet one of the key eligibility criteria.
Showcase Relevant Experience: Detail your hands-on experience with data science and machine learning. Include specific projects where you've designed, developed, and deployed models, as well as any tools or frameworks you've used, such as Python, pandas, or TensorFlow.
Emphasise Collaboration Skills: This role requires collaboration with various stakeholders. Highlight any previous experiences where you've worked closely with data analysts, engineers, or other teams to enhance workflows or innovate solutions.
Tailor Your Application: Customise your CV and cover letter to reflect the responsibilities and skills mentioned in the job description. Use keywords from the listing to demonstrate that you understand the role and are a perfect fit.
How to prepare for a job interview at Korn Ferry
✨Showcase Your DV Clearance
Since this role requires active DV clearance, make sure to mention your status early in the conversation. This will reassure the interviewers that you meet one of the key eligibility criteria.
✨Demonstrate Your Technical Skills
Be prepared to discuss your experience with Python and its data/ML ecosystem. Bring examples of projects where you've used libraries like pandas, scikit-learn, or TensorFlow, and be ready to explain your thought process and the impact of your work.
✨Discuss the Full ML Life Cycle
Highlight your familiarity with the entire machine learning life cycle. Talk about specific instances where you've taken a model from development through to deployment and monitoring, showcasing your ability to handle each stage effectively.
✨Collaboration is Key
Emphasise your experience working with cross-functional teams. Share examples of how you've collaborated with data analysts, engineers, or other stakeholders to enhance workflows and drive innovation, as teamwork is crucial in this role.
